MedWorm: Bioinformatics

Deterministic graph-theoretic algorithm for detecting modules in biological interaction networks.

International Journal of Bioinformatics Research and Applications — Sat, 13 Mar 2010 19:32:02 +0100

Authors: Chang RL, Luo F, Johnson S, Scheuermann RH An approach for module identification, Modules of Networks (MoNet), introduced an intuitive module definition and clear detection method using edges ranked by the Girvan-Newman algorithm. Modules from a yeast network showed significant association with biological processes, indicating the method's utility; however, systematic bias leads to varied results across trials. MoNet modules also exclude some network regions. To address these shortcomings, we developed a deterministic version of the Girvan-Newman algorithm and a new agglomerative algorithm, Deterministic Modularization of Networks (dMoNet). dMoNet simultaneously processes structurally equivalent edges while preserving intuitive foundations of the MoNet algorithm and generates ...

MedWorm Message: Get the very latest Swine Flu news via the MedWorm Swine Flu RSS news feed - updated hourly from thousands of authoritative health and news sources.

Assessing and improving the accuracy of detecting protein adaptation with the TreeSAAP analytical software.

International Journal of Bioinformatics Research and Applications — Sat, 13 Mar 2010 19:32:02 +0100

Authors: McClellan DA, Ellison DD TreeSAAP has been used in a variety of protein studies for detecting adaptation in terms of the physicochemical properties involved in amino acid replacement. The accuracy of TreeSAAP was here tested using simulated protein-coding DNA data. A sampling of 1402 simulated amino acid replacements resulted in a default accuracy of 81.1%, with most properties exhibiting >90% accuracy. More than half of the false-positive results were traced to just 11 of the 180 possible single-step amino acid exchanges. Overall accuracy increased as the number of magnitude partitions used in the analysis decreased. Sliding window size did not significantly affect accuracy. PMID: 20223735 [PubMed - in process] (Source: International Journal of Bioinformatics Research ...

Flavitrack analysis of the structure and function of West Nile non-structural proteins.

International Journal of Bioinformatics Research and Applications — Sat, 13 Mar 2010 19:32:02 +0100

Authors: Danecek P, Schein CH The Flavitrack database groups Flaviviruses (FV), evolutionarily related organisms with high subtype variability, according to their phenotypes. Here, PCPMer tools were used to calculate consensus sequences based on conservation of Physicochemical Properties (PCP) for 919 sequences of NS2a, a non-structural protein involved in preventing host interferon response to infection. Conserved PCP-motifs were detected, primarily in the N-terminal half of NS2a. One model structure, based on a nuclear receptor, groups residues essential for West Nile (WN) infectivity (I59, V61, and M103) in a pocket on the protein surface. These methods will aid in the design of vaccines and specific therapies against FV. PMID: 20223736 [PubMed - in process] (Source: Internation...

An algorithm for the reconstruction of consensus sequences of ancient segmental duplications and transposon copies in eukaryotic genomes.

International Journal of Bioinformatics Research and Applications — Sat, 13 Mar 2010 19:32:02 +0100

Authors: Singh A, Keswani U, Levine D, Feschotte C, Interspersed repeats, mostly resulting from the activity and accumulation of transposable elements, occupy a significant fraction of many eukaryotic genomes. More than half of human genomic sequence consists of known repeats, however a very large part has not yet been associated with neither repetitive structures nor functional units. We have postulated that most of the seemingly unique content of mammalian genomes is also a result of transposon activity, written software to look for weak signals which would help us reconstruct the ancient elements with substantially mutated copies, and integrated it into a system for de novo identification and classification of interspersed repeats. In this manuscript we describe our approach, and r...

Strategies for enhanced annotation of a microarray probe set.

International Journal of Bioinformatics Research and Applications — Sat, 13 Mar 2010 19:32:02 +0100

Authors: Powers TR, Virk SM, Serrano EE We aim to determine the biological relevance of genes identified through microarray-mediated transcriptional profiling of Xenopus sensory organs and brain. Difficulties with genetic data analysis arise because of limitations in probe set annotation and the lack of a universal gene nomenclature. To overcome these impediments, we used sequence based and semantic linking methods in combination with computational approaches to augment probe set annotation on a commercially available microarray. Our curation efforts enabled linkage of probe sets and expression data to public databases, increased the biological significance of our microarray data, and assisted with the tentative identification of unidentified probe sets. PMID: 20223738 [PubMed - in...

Ranking through integration of protein-similarity for identification of cell-cyclic genes.

International Journal of Bioinformatics Research and Applications — Sat, 13 Mar 2010 19:32:02 +0100

We present a unique schema to enable integration by employing QR-factorisation from the pair-wise similarity matrix formulation. Angular coefficients are derived and consequently employed for integrated gene ranking. Experimental results on an independent benchmark dataset signify the efficacy of the method. PMID: 20223739 [PubMed - in process] (Source: International Journal of Bioinformatics Research and Applications)

MedWorm Message: Get the very latest Swine Flu news via the MedWorm Swine Flu RSS news feed - updated hourly from thousands of authoritative health and news sources.

Scalable biomedical Named Entity Recognition: investigation of a database-supported SVM approach.

International Journal of Bioinformatics Research and Applications — Sat, 13 Mar 2010 19:32:02 +0100

Authors: Habib MS, Kalita J This paper explores scalability issues associated with the Named Entity Recognition problem in the biomedical publications domain using Support Vector Machines. The performance results using existing binary and multi-class SVMs with increasing training data are compared to results obtained using our new implementations. Our approach eliminates prior language or domain-specific knowledge and achieves good out-of-the-box accuracy measures comparable to those obtained using more complex approaches. The training time of multi-class SVMs is reduced by several orders of magnitude, which would make support vector machines a more viable and practical solution for real-world problems with large datasets. PMID: 20223740 [PubMed - in process] (Source: International...

Mining Cytochrome b561 proteins from plant genomes.

International Journal of Bioinformatics Research and Applications — Sat, 13 Mar 2010 19:32:02 +0100

Authors: Opiyo SO, Moriyama EN Cytochrome b561 (Cyt-b561) proteins are important for plant growth, development, and prevention of damage to plants. Because of their high sequence divergence, thorough mining of Cyt-b561 proteins from plant genomes are not easy. Currently there is only one Cyt-b561 gene found in the maize and none in the soybean genome. However, 22 have been identified in the Arabidopsis thaliana genome. We tested alignment-free protein classifiers based on partial least squares (PLS) and support vector machines to identify Cyt-b561. These classifiers performed better than profile hidden Markov models and PSI-BLAST. Using these classifiers we identified new Cyt-b561-related proteins from four plant genomes. PMID: 20223741 [PubMed - in process] (Source: International ...

Interactions Between the Immune System and Cancer: A Brief Review of Non-spatial Mathematical Models.

Bulletin of Mathematical Biology — Fri, 12 Mar 2010 00:00:00 +0100

Authors: Eftimie R, Bramson JL, Earn DJ We briefly review spatially homogeneous mechanistic mathematical models describing the interactions between a malignant tumor and the immune system. We begin with the simplest (single equation) models for tumor growth and proceed to consider greater immunological detail (and correspondingly more equations) in steps. This approach allows us to clarify the necessity for expanding the complexity of models in order to capture the biological mechanisms we wish to understand. We conclude by discussing some unsolved problems in the mathematical modeling of cancer-immune system interactions. PMID: 20225137 [PubMed - as supplied by publisher] (Source: Bulletin of Mathematical Biology)

Proteomic analysis of PBMCs: characterization of potential HIV-associated proteins

Proteome Science — Fri, 12 Mar 2010 00:00:00 +0100

Conclusions: Together, this work provided useful information to facilitate further investigation of the underlying mechanism of HIV and host cell protein interactions, and discovered novel potential biomarkers such as fragment of vinculin, filamin-A and talin-1 for anti-HIV research. (Source: Proteome Science)

Mocapy++ - A toolkit for inference and learning in dynamic Bayesian networks

BMC Bioinformatics - Latest articles — Fri, 12 Mar 2010 00:00:00 +0100

Conclusions: Mocapy++ is especially suitable for constructing probabilistic models of biomolecular structure, due to its support for directional statistics. In particular, it supports the Kent distribution on the sphere and the bivariate von Mises distribution on the torus. These distributions have proven useful to formulate probabilistic models of protein and RNA structure in atomic detail. (Source: BMC Bioinformatics - Latest articles)

MedWorm Message: Get the very latest Swine Flu news via the MedWorm Swine Flu RSS news feed - updated hourly from thousands of authoritative health and news sources.

New statistical potential for quality assessment of protein models and a survey of energy functions

BMC Bioinformatics - Latest articles — Fri, 12 Mar 2010 00:00:00 +0100

Conclusions: Among the most influential terms we observed a critical role of a proper reference state definition and the benefits of including information about the microenvironment of interaction centers. Molecular mechanical potentials were also tested and found to be over-sensitive to small local imperfections in a structure, requiring unfeasible long energy relaxation before energy scores started to correlate with model quality. (Source: BMC Bioinformatics - Latest articles)

KiDoQ: using docking based energy scores to develop ligand based model for predicting antibacterials

BMC Bioinformatics - Latest articles — Thu, 11 Mar 2010 00:00:00 +0100

Conclusions: Our results suggests that ligand-receptor binding interactions for DHDPS employing QSAR modeling seems to be a promising approach for prediction of antibacterial agents. To serve the experimentalist to develop novel/potent inhibitors, a webserver "KiDoQ" has been developed (http://crdd.osdd.net/raghava/kidoq), which allows the prediction of Ki value of a new ligand molecule against DHDPS. (Source: BMC Bioinformatics - Latest articles)

A fast and robust hepatocyte quantification algorithm including vein processing

BMC Bioinformatics - Latest articles — Wed, 10 Mar 2010 00:00:00 +0100

Conclusions: The proposed automatic procedure gives results with high sensitivity and low false positive fractionand can be applied to process entire stained sections. (Source: BMC Bioinformatics - Latest articles)

Enhancing metabolomic data analysis with Progressive Consensus Alignment of NMR Spectra (PCANS)

BMC Bioinformatics - Latest articles — Tue, 09 Mar 2010 00:00:00 +0100

Conclusions: By avoiding the use of a template or reference spectrum, PCANS allows for the creation of a consensus spectrum that enhances the signals within the spectra while maintaining sample-specific features. This approach is of greatest benefit when complex samples are being analyzed and where it is expected that there will be spectral features unique and/or strongly different between subgroups within the samples. Furthermore, this approach can be potentially applied to the alignment of any data having spectra-like properties. (Source: BMC Bioinformatics - Latest articles)

SCPS: a fast implementation of a spectral method for detecting protein families on a genome-wide scale

BMC Bioinformatics - Latest articles — Tue, 09 Mar 2010 00:00:00 +0100

Conclusions: Besides the spectral method, SCPS also implements connected component analysis and hierarchical clustering, it integrates TribeMCL, it provides different cluster quality tools, it can extract human-readable protein descriptions using GI numbers from NCBI, it interfaces with external tools such as BLAST and Cytoscape, and it can produce publication-quality graphical representations of the clusters obtained, thus constituting a comprehensive and effective tool for practical research in computational biology. Source code and precompiled executables for Windows, Linux and Mac OS X are freely available at http://www.paccanarolab.org/software/scps. (Source: BMC Bioinformatics - Latest articles)

MedWorm Message: Get the very latest Swine Flu news via the MedWorm Swine Flu RSS news feed - updated hourly from thousands of authoritative health and news sources.

Testing the Coding Potential of Conserved Short Genomic Sequences

Advances in Bioinformatics — Mon, 08 Mar 2010 17:55:04 +0100

Proposed is a procedure to test whether a genomic sequence contains coding DNA, called a coding potential region. The procedure tests the coding potential of conserved short genomic sequence, in which the assumptions on the probability models of gene structures are relaxed. Thus, it is expected to provide additional candidate regions that contain coding DNAs to the current genomic database. The procedure was applied to the set of highly conserved human-mouse sequences in the genome database at the University of California at Santa Cruz. For sequences containing RefSeq coding exons, the procedure detected 91.3% regions having coding potential in this set, which covers 83% of the human RefSeq coding exons, at a 2.6% false positive rate. The procedure detected 12,688 novel short r...

Prodigal: prokaryotic gene recognition and translation initiation site identification

BMC Bioinformatics - Latest articles — Mon, 08 Mar 2010 00:00:00 +0100

Conclusion: We built a fast, lightweight, open source gene prediction program called Prodigal (http://compbio.ornl.gov/prodigal/). Prodigal achieved good results compared to existing methods, and we believe it will be a valuable asset to automated microbial annotation pipelines. (Source: BMC Bioinformatics - Latest articles)

Network Properties for Ranking Predicted miRNA Targets in Breast Cancer

Advances in Bioinformatics — Sun, 07 Mar 2010 16:19:19 +0100

MicroRNAs control the expression of their target genes by translational repression and transcriptional cleavage. They are involved in various biological processes including development and progression of cancer. To uncover the biological role of miRNAs it is important to identify their target genes. The small number of experimentally validated target genes makes computer prediction methods very important. However, state-of-the-art prediction tools result in a great number of putative targets with an unpredictable number of false positives. In this paper, we propose and evaluate two approaches for ranking the biological relevance of putative targets of miRNAs which are associated with breast cancer. (Source: Advances in Bioinformatics)

GPU computing for systems biology.

Briefings in Bioinformatics — Sun, 07 Mar 2010 00:00:00 +0100

Authors: Dematté L, Prandi D The development of detailed, coherent, models of complex biological systems is recognized as a key requirement for integrating the increasing amount of experimental data. In addition, in-silico simulation of bio-chemical models provides an easy way to test different experimental conditions, helping in the discovery of the dynamics that regulate biological systems. However, the computational power required by these simulations often exceeds that available on common desktop computers and thus expensive high performance computing solutions are required. An emerging alternative is represented by general-purpose scientific computing on graphics processing units (GPGPU), which offers the power of a small computer cluster at a cost of approximately $400. Comp...

PrePrint: Prediction of Protein Functions with Gene Ontology and Inter-Species Protein Homology Data

IEEE/ACM Transactions on Computational Biology and Bioinformatics — Sat, 06 Mar 2010 11:00:01 +0100

Accurate computational prediction of protein functions increasingly relies on network-inspired models for the protein function transfer. This task can become challenging for proteins isolated in their own network or those with poor or uncharacterized neighborhoods. Here, we present a novel probabilistic chain-graph based approach for predicting protein functions that builds on connecting networks of two (or more) different species by links of high inter-species sequence homology. In this way, proteins are able to "exchange" functional information with their neighbors-homologs from a different species. The knowledge of inter-species relationships, such as the sequence homology, can become crucial in cases of limited information from other sources of data, including the protein-protein inter...

MedWorm Message: Get the very latest Swine Flu news via the MedWorm Swine Flu RSS news feed - updated hourly from thousands of authoritative health and news sources.

Biological network comparison using graphlet degree distribution

Bioinformatics — Fri, 05 Mar 2010 12:22:08 +0100

(Source: Bioinformatics)

Easy retrieval of single amino-acid polymorphisms and phenotype information using SwissVar

Bioinformatics — Fri, 05 Mar 2010 12:22:08 +0100

Summary: The SwissVar portal provides access to a comprehensive collection of single amino acid polymorphisms and diseases in the UniProtKB/Swiss-Prot database via a unique search engine. In particular, it gives direct access to the newly improved Swiss-Prot variant pages. The key strength of this portal is that it provides a possibility to query for similar diseases, as well as the underlying protein products and the molecular details of each variant. In the context of the recently proposed molecular view on diseases, the SwissVar portal should be in a unique position to provide valuable information for researchers and to advance research in this area. Availability: The SwissVar portal is available at www.expasy.org/swissvar Contact: anais.mottaz@isb-sib.ch; lina.yip@isb-sib.ch Supplement...

Filtering error from SOLiD Output

Bioinformatics — Fri, 05 Mar 2010 12:22:08 +0100

Summary: Here, we report the development of a filtering framework designed for efficient identification of both polyclonal and independent errors within SOLiD sequence data. The filtering utilizes the quality values reported by SOLiD's primary analysis for the identification of the two different types of errors. The filtering framework facilitates the passage of high-quality data into a variety of functional genomics applications, including de novo assemblers and sequence matching programs for SNP calling, improving the output quality and reducing resources necessary for analysis. Availability: This error analysis framework is written in Perl and runs on Mac OS and Linux/Unix systems. The filter, documentation and sample Excel files for quality analysis are available at http://hts.rutgers....

XDIA: improving on the label-free data-independent analysis

Bioinformatics — Fri, 05 Mar 2010 12:22:08 +0100

Summary: XDIA is a computational strategy for analyzing multiplexed spectra acquired using electron transfer dissociation and collision-activated dissociation; it significantly increases identified spectra (~250%) and unique peptides (~30%) when compared with the data-dependent ETCaD analysis on middle-down, single-phase shotgun proteomic analysis. Increasing identified spectra and peptides improves quantitation statistics confidence and protein coverage, respectively. Availability: The software and data produced in this work are freely available for academic use at http://fields.scripps.edu/XDIA Contact: paulo@pcarvalho.com Supplementary information: Supplementary data are available at Bioinformatics online. (Source: Bioinformatics)

FineStr: a web server for single-base-resolution nucleosome positioning

Bioinformatics — Fri, 05 Mar 2010 12:22:08 +0100

Summary: The DNA in eukaryotic cells is packed into the chromatin that is composed of nucleosomes. Positioning of the nucleosome core particles on the sequence is a problem of great interest because of the role nucleosomes play in different cellular processes including gene regulation. Using the sequence structure of 10.4 base DNA repeat presented in our previous works and nucleosome core DNA sequences database, we have derived the complete nucleosome DNA bendability matrix of Caenorhabditis elegans. We have developed a web server named FineStr that allows users to upload genomic sequences in FASTA format and to perform a single-base-resolution nucleosome mapping on them. Availability: FineStr server is freely available for use on the web at http:/www.cs.bgu.ac.il/~nucleom. The site contai...

MedWorm Message: Get the very latest Swine Flu news via the MedWorm Swine Flu RSS news feed - updated hourly from thousands of authoritative health and news sources.

iMotifs: an integrated sequence motif visualization and analysis environment

Bioinformatics — Fri, 05 Mar 2010 12:22:08 +0100

Motivation: Short sequence motifs are an important class of models in molecular biology, used most commonly for describing transcription factor binding site specificity patterns. High-throughput methods have been recently developed for detecting regulatory factor binding sites in vivo and in vitro and consequently high-quality binding site motif data are becoming available for increasing number of organisms and regulatory factors. Development of intuitive tools for the study of sequence motifs is therefore important. iMotifs is a graphical motif analysis environment that allows visualization of annotated sequence motifs and scored motif hits in sequences. It also offers motif inference with the sensitive NestedMICA algorithm, as well as overrepresentation and pairwise motif matching capabi...

BEDTools: a flexible suite of utilities for comparing genomic features

Bioinformatics — Fri, 05 Mar 2010 12:22:08 +0100

This article introduces a new software suite for the comparison, manipulation and annotation of genomic features in Browser Extensible Data (BED) and General Feature Format (GFF) format. BEDTools also supports the comparison of sequence alignments in BAM format to both BED and GFF features. The tools are extremely efficient and allow the user to compare large datasets (e.g. next-generation sequencing data) with both public and custom genome annotation tracks. BEDTools can be combined with one another as well as with standard UNIX commands, thus facilitating routine genomics tasks as well as pipelines that can quickly answer intricate questions of large genomic datasets. Availability and implementation: BEDTools was written in C++. Source code and a comprehensive user manual are freely avai...

invertFREGENE: software for simulating inversions in population genetic data

Bioinformatics — Fri, 05 Mar 2010 12:22:07 +0100

We describe previously unreported signatures of inversions in SNP data observed in invertFREGENE results and a known inversion in humans. Availability: C++ source code and user manual are available for download from http://www.ebi.ac.uk/projects/BARGEN/ under the GPL licence. Contact: l.coin@ic.ac.uk; c.hoggart@ic.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online. (Source: Bioinformatics)

Maximal conditional chi-square importance in random forests

Bioinformatics — Fri, 05 Mar 2010 12:22:07 +0100

Motivation: High-dimensional data are frequently generated in genome-wide association studies (GWAS) and other studies. It is important to identify features such as single nucleotide polymorphisms (SNPs) in GWAS that are associated with a disease. Random forests represent a very useful approach for this purpose, using a variable importance score. This importance score has several shortcomings. We propose an alternative importance measure to overcome those shortcomings. Results: We characterized the effect of multiple SNPs under various models using our proposed importance measure in random forests, which uses maximal conditional chi-square (MCC) as a measure of association between a SNP and the trait conditional on other SNPs. Based on this importance measure, we employed a permutation tes...

Small-sample precision of ROC-related estimates

Bioinformatics — Fri, 05 Mar 2010 12:22:07 +0100

Motivation: The receiver operator characteristic (ROC) curves are commonly used in biomedical applications to judge the performance of a discriminant across varying decision thresholds. The estimated ROC curve depends on the true positive rate (TPR) and false positive rate (FPR), with the key metric being the area under the curve (AUC). With small samples these rates need to be estimated from the training data, so a natural question arises: How well do the estimates of the AUC, TPR and FPR compare with the true metrics? Results: Through a simulation study using data models and analysis of real microarray data, we show that (i) for small samples the root mean square differences of the estimated and true metrics are considerable; (ii) even for large samples, there is only weak correlation be...

MedWorm Message: Get the very latest Swine Flu news via the MedWorm Swine Flu RSS news feed - updated hourly from thousands of authoritative health and news sources.

Predicting biodegradation products and pathways: a hybrid knowledge- and machine learning-based approach

Bioinformatics — Fri, 05 Mar 2010 12:22:07 +0100

Motivation: Current methods for the prediction of biodegradation products and pathways of organic environmental pollutants either do not take into account domain knowledge or do not provide probability estimates. In this article, we propose a hybrid knowledge- and machine learning-based approach to overcome these limitations in the context of the University of Minnesota Pathway Prediction System (UM-PPS). The proposed solution performs relative reasoning in a machine learning framework, and obtains one probability estimate for each biotransformation rule of the system. As the application of a rule then depends on a threshold for the probability estimate, the trade-off between recall (sensitivity) and precision (selectivity) can be addressed and leveraged in practice. Results: Results from ...

Prediction of human functional genetic networks from heterogeneous data using RVM-based ensemble learning

Bioinformatics — Fri, 05 Mar 2010 12:22:07 +0100

Motivation: Three major problems confront the construction of a human genetic network from heterogeneous genomics data using kernel-based approaches: definition of a robust gold-standard negative set, large-scale learning and massive missing data values. Results: The proposed graph-based approach generates a robust GSN for the training process of genetic network construction. The RVM-based ensemble model that combines AdaBoost and reduced-feature yields improved performance on large-scale learning problems with massive missing values in comparison to Naïve Bayes. Contact: dargenio@bmsr.usc.edu Supplementary information: Supplementary material is available at Bioinformatics online. (Source: Bioinformatics)

Correcting population stratification in genetic association studies using a phylogenetic approach

Bioinformatics — Fri, 05 Mar 2010 12:22:07 +0100

We report PHYLOSTRAT, a new method that corrects for population stratification by combining phylogeny constructed from SNP genotypes and principal coordinates from multi-dimensional scaling (MDS) analysis. This hybrid approach efficiently captures both discrete and admixed population structures. Results: By extensive simulations, the analysis of a synthetic genome-wide association dataset created using data from the Human Genome Diversity Project, and the analysis of a lactase-height dataset, we show that our method can correct for population stratification more efficiently than several existing population stratification correction methods, including EIGENSTRAT, a hybrid approach based on MDS and clustering, and STRATSCORE , in terms of requiring fewer random SNPs for inference of populati...

Non-linear classification for on-the-fly fractional mass filtering and targeted precursor fragmentation in mass spectrometry experiments

Bioinformatics — Fri, 05 Mar 2010 12:22:07 +0100

Motivation: Mass spectrometry (MS) has become the method of choice for protein/peptide sequence and modification analysis. The technology employs a two-step approach: ionized peptide precursor masses are detected, selected for fragmentation, and the fragment mass spectra are collected for computational analysis. Current precursor selection schemes are based on data- or information-dependent acquisition (DDA/IDA), where fragmentation mass candidates are selected by intensity and are subsequently included in a dynamic exclusion list to avoid constant refragmentation of highly abundant species. DDA/IDA methods do not exploit valuable information that is contained in the fractional mass of high-accuracy precursor mass measurements delivered by current instrumentation. Results: We extend previo...

Gene selection in microarray survival studies under possibly non-proportional hazards

Bioinformatics — Fri, 05 Mar 2010 12:22:07 +0100

Motivation: Univariate Cox regression (COX) is often used to select genes possibly linked to survival. With non-proportional hazards (NPH), COX could lead to under- or over-estimation of effects. The effect size measure c=P(T1<T0), i.e. the probability that a person randomly chosen from group G1 dies earlier than a person from G0, is independent of the proportional hazards (PH) assumption. Here we consider its generalization to continuous data c' and investigate the suitability of c' for gene selection. Results: Under PH, c' is most efficiently estimated by COX. Under NPH, c' can be obtained by weighted Cox regression (WHE) or a novel method, concordance regression (CON). The least biased and most stable estimates were obtained by CON. We propose to use c' as summary measure of effect s...

MedWorm Message: Get the very latest Swine Flu news via the MedWorm Swine Flu RSS news feed - updated hourly from thousands of authoritative health and news sources.

A hidden Ising model for ChIP-chip data analysis

Bioinformatics — Fri, 05 Mar 2010 12:22:07 +0100

Motivation: Chromatin immunoprecipitation (ChIP) coupled with tiling microarray (chip) experiments have been used in a wide range of biological studies such as identification of transcription factor binding sites and investigation of DNA methylation and histone modification. Hidden Markov models are widely used to model the spatial dependency of ChIP-chip data. However, parameter estimation for these models is typically either heuristic or suboptimal, leading to inconsistencies in their applications. To overcome this limitation and to develop an efficient software, we propose a hidden ferromagnetic Ising model for ChIP-chip data analysis. Results: We have developed a simple, but powerful Bayesian hierarchical model for ChIP-chip data via a hidden Ising model. Metropolis within Gibbs sampli...

Estimating replicate time shifts using Gaussian process regression

Bioinformatics — Fri, 05 Mar 2010 12:22:07 +0100

Motivation: Time-course gene expression datasets provide important insights into dynamic aspects of biological processes, such as circadian rhythms, cell cycle and organ development. In a typical microarray time-course experiment, measurements are obtained at each time point from multiple replicate samples. Accurately recovering the gene expression patterns from experimental observations is made challenging by both measurement noise and variation among replicates' rates of development. Prior work on this topic has focused on inference of expression patterns assuming that the replicate times are synchronized. We develop a statistical approach that simultaneously infers both (i) the underlying (hidden) expression profile for each gene, as well as (ii) the biological time for each individual ...

Extraction and comparison of gene expression patterns from 2D RNA in situ hybridization images

Bioinformatics — Fri, 05 Mar 2010 12:22:07 +0100

Motivation: Recent advancements in high-throughput imaging have created new large datasets with tens of thousands of gene expression images. Methods for capturing these spatial and/or temporal expression patterns include in situ hybridization or fluorescent reporter constructs or tags, and results are still frequently assessed by subjective qualitative comparisons. In order to deal with available large datasets, fully automated analysis methods must be developed to properly normalize and model spatial expression patterns. Results: We have developed image segmentation and registration methods to identify and extract spatial gene expression patterns from RNA in situ hybridization experiments of Drosophila embryos. These methods allow us to normalize and extract expression information for 78 ...

Cascleave: towards more accurate prediction of caspase substrate cleavage sites

Bioinformatics — Fri, 05 Mar 2010 12:22:07 +0100

Motivation: The caspase family of cysteine proteases play essential roles in key biological processes such as programmed cell death, differentiation, proliferation, necrosis and inflammation. The complete repertoire of caspase substrates remains to be fully characterized. Accordingly, systematic computational screening studies of caspase substrate cleavage sites may provide insight into the substrate specificity of caspases and further facilitating the discovery of putative novel substrates. Results: In this article we develop an approach (termed Cascleave) to predict both classical (i.e. following a P1 Asp) and non-typical caspase cleavage sites. When using local sequence-derived profiles, Cascleave successfully predicted 82.2% of the known substrate cleavage sites, with a Matthews correl...

A fast and automated solution for accurately resolving protein domain architectures

Bioinformatics — Fri, 05 Mar 2010 12:22:07 +0100

Motivation: Accurate prediction of the domain content and arrangement in multi-domain proteins (which make up >65% of the large-scale protein databases) provides a valuable tool for function prediction, comparative genomics and studies of molecular evolution. However, scanning a multi-domain protein against a database of domain sequence profiles can often produce conflicting and overlapping matches. We have developed a novel method that employs heaviest weighted clique-finding (HCF), which we show significantly outperforms standard published approaches based on successively assigning the best non-overlapping match (Best Match Cascade, BMC). Results: We created benchmark data set of structural domain assignments in the CATH database and a corresponding set of Hidden Markov Model-based do...

MedWorm Message: Get the very latest Swine Flu news via the MedWorm Swine Flu RSS news feed - updated hourly from thousands of authoritative health and news sources.

A visual framework for sequence analysis using n-grams and spectral rearrangement

Bioinformatics — Fri, 05 Mar 2010 12:22:07 +0100

Motivation: Protein sequences are often composed of regions that have distinct evolutionary histories as a consequence of domain shuffling, recombination or gene conversion. New approaches are required to discover, visualize and analyze these sequence regions and thus enable a better understanding of protein evolution. Results: Here, we have developed an alignment-free and visual approach to analyze sequence relationships. We use the number of shared n-grams between sequences as a measure of sequence similarity and rearrange the resulting affinity matrix applying a spectral technique. Heat maps of the affinity matrix are employed to identify and visualize clusters of related sequences or outliers, while n-gram-based dot plots and conservation profiles allow detailed analysis of similaritie...

SNVMix: predicting single nucleotide variants from next-generation sequencing of tumors

Bioinformatics — Fri, 05 Mar 2010 12:22:07 +0100

Motivation: Next-generation sequencing (NGS) has enabled whole genome and transcriptome single nucleotide variant (SNV) discovery in cancer. NGS produces millions of short sequence reads that, once aligned to a reference genome sequence, can be interpreted for the presence of SNVs. Although tools exist for SNV discovery from NGS data, none are specifically suited to work with data from tumors, where altered ploidy and tumor cellularity impact the statistical expectations of SNV discovery. Results: We developed three implementations of a probabilistic Binomial mixture model, called SNVMix, designed to infer SNVs from NGS data from tumors to address this problem. The first models allelic counts as observations and infers SNVs and model parameters using an expectation maximization (EM) algori...

Microindel detection in short-read sequence data

Bioinformatics — Fri, 05 Mar 2010 12:22:07 +0100

Motivation: Several recent studies have demonstrated the effectiveness of resequencing and single nucleotide variant (SNV) detection by deep short-read sequencing platforms. While several reliable algorithms are available for automated SNV detection, the automated detection of microindels in deep short-read data presents a new bioinformatics challenge. Results: We systematically analyzed how the short-read mapping tools MAQ, Bowtie, Burrows-Wheeler alignment tool (BWA), Novoalign and RazerS perform on simulated datasets that contain indels and evaluated how indels affect error rates in SNV detection. We implemented a simple algorithm to compute the equivalent indel region eir, which can be used to process the alignments produced by the mapping tools in order to perform indel calling. Using...

Identifying biologically relevant differences between metagenomic communities

Bioinformatics — Fri, 05 Mar 2010 12:22:07 +0100

Motivation: Metagenomics is the study of genetic material recovered directly from environmental samples. Taxonomic and functional differences between metagenomic samples can highlight the influence of ecological factors on patterns of microbial life in a wide range of habitats. Statistical hypothesis tests can help us distinguish ecological influences from sampling artifacts, but knowledge of only the P-value from a statistical hypothesis test is insufficient to make inferences about biological relevance. Current reporting practices for pairwise comparative metagenomics are inadequate, and better tools are needed for comparative metagenomic analysis. Results: We have developed a new software package, STAMP, for comparative metagenomics that supports best practices in analysis and reporting...

Six Rossmannoid folds, including the Class I aminoacyl-tRNA synthetases, share a partial core with the anti-codon-binding domain of a Class II aminoacyl-tRNA synthetase

Bioinformatics — Fri, 05 Mar 2010 12:22:07 +0100

Motivation: Similarities in core residue packing provide evidence for divergence or convergence not reported using other methods. Results: We apply a new method for rapid structure comparison based on Simplicial Neighborhood Analysis of Protein Packing (SNAPP) to the diverse structural classification of proteins (SCOP) /β-class of protein folds. The procedure identifies inter-residue packing motifs shared by protein pairs from different folds. A threshold of 0.67 Å RMSD for all atoms of corresponding residues ensures inclusion of only highly significant similarities comparable with those observed for identical catalytic residues in homologues. Many tertiary packing motifs are shared among the three classical Rossmannoid folds, as well as thousands of other motifs that occur in a...

MedWorm Message: Get the very latest Swine Flu news via the MedWorm Swine Flu RSS news feed - updated hourly from thousands of authoritative health and news sources.

Asymptotics of Conduction Velocity Restitution in Models of Electrical Excitation in the Heart.

Bulletin of Mathematical Biology — Fri, 05 Mar 2010 00:00:00 +0100

Authors: Simitev RD, Biktashev VN We extend a non-Tikhonov asymptotic embedding, proposed earlier, for calculation of conduction velocity restitution curves in ionic models of cardiac excitability. Conduction velocity restitution is the simplest non-trivial spatially extended problem in excitable media, and in the case of cardiac tissue it is an important tool for prediction of cardiac arrhythmias and fibrillation. An idealized conduction velocity restitution curve requires solving a non-linear eigenvalue problem with periodic boundary conditions, which in the cardiac case is very stiff and calls for the use of asymptotic methods. We compare asymptotics of restitution curves in four examples, two generic excitable media models, and two ionic cardiac models. The generic models include t...

Mathematical Model of Hyperbaric Oxygen Therapy Applied to Chronic Diabetic Wounds.

Bulletin of Mathematical Biology — Fri, 05 Mar 2010 00:00:00 +0100

Authors: Flegg JA, Byrne HM, McElwain DL The failure of certain wounds to heal (including diabetic foot ulcers) is a significant socioeconomic issue for countries worldwide. There is much debate about the best way to treat these wounds and one approach that is shrouded with controversy is hyperbaric oxygen therapy (HBOT), a technique that can reduce the risk of amputation in diabetic patients.In this paper, we develop a six species mathematical model of wound healing angiogenesis and use it to investigate the effectiveness of HBOT, compare the response to different HBOT protocols and study the effect of HBOT on the healing of diabetic wounds that fail to heal for a variety of reasons. We vary the pressure level (1 atm-3 atm), percentage of oxygen inspired by the patient (21%-100%), ses...

A high-throughput de novo sequencing approach for shotgun proteomics using high-resolution tandem mass spectrometry

BMC Bioinformatics - Latest articles — Fri, 05 Mar 2010 00:00:00 +0100

Conclusions: Here, we improved de novo sequencing performance by developing a new algorithm specifically for high-resolution tandem mass spectral data. The Vonode algorithm is freely available for download at http://compbio.ornl.gov/Vonode. (Source: BMC Bioinformatics - Latest articles)

Selection of Statistical Thresholds in Graphical Models

EURASIP Journal on Bioinformatics and Systems Biology — Thu, 04 Mar 2010 18:22:46 +0100

Reconstruction of gene regulatory networks based on experimental data usually relies on statistical evidence, necessitating the choice of a statistical threshold which defines a significant biological effect. Approaches to this problem found in the literature range from rigorous multiple testing procedures to ad hoc P-value cut-off points. However, when the data implies graphical structure, it should be possible to exploit this feature in the threshold selection process. In this article we propose a procedure based on this principle. Using coding theory we devise a measure of graphical structure, for example, highly connected nodes or chain structure. The measure for a particular graph can be compared to that of a random graph and structure inferred on that basis. By varying the statistica...

Python Testing Beginner’s Guide, review

Beginning Python for Bioinformatics — Thu, 04 Mar 2010 03:46:35 +0100

I posted about a week ago that Packt Publishing had invited me to review Python Testing Beginner’s Guide by Daniel Arbuckle. Having finished reading the book (I must admit that I haven’t tried all the code in it), I can say that I have an excellent initial impression of the book. PTBG is not a long book and the topic is divided in 10 chapters and one appendix. One of the first things that I liked about the book is that there’s no introduction (or something similar) to Python. It just goes straight to the point assuming that you have some good understanding of the language and everything that surrounds it. In the past I was frustrated with some “Introduction to X with Python” that wasted precious space talking over and over about a topic, learning Python, bette...

MedWorm Message: Get the very latest Swine Flu news via the MedWorm Swine Flu RSS news feed - updated hourly from thousands of authoritative health and news sources.

Modeling Optimal Intervention Strategies for Cholera.

Bulletin of Mathematical Biology — Thu, 04 Mar 2010 00:00:00 +0100

Authors: Miller Neilan RL, Schaefer E, Gaff H, Fister KR, Lenhart S While cholera has been a recognized disease for two centuries, there is no strategy for its effective control. We formulate a mathematical model to include essential components such as a hyperinfectious, short-lived bacterial state, a separate class for mild human infections, and waning disease immunity. A new result quantifies contributions to the basic reproductive number from multiple infectious classes. Using optimal control theory, parameter sensitivity analysis, and numerical simulations, a cost-effective balance of multiple intervention methods is compared for two endemic populations. Results provide a framework for designing cost-effective strategies for diseases with multiple intervention methods. PMID: 20...

Ensemble learning algorithms for classification of mtDNA into haplogroups.

Briefings in Bioinformatics — Thu, 04 Mar 2010 00:00:00 +0100

Authors: Wong C, Li Y, Lee C, Huang CH Classification of mitochondrial DNA (mtDNA) into their respective haplogroups allows the addressing of various anthropologic and forensic issues. Unique to mtDNA is its abundance and non-recombining uni-parental mode of inheritance; consequently, mutations are the only changes observed in the genetic material. These individual mutations are classified into their cladistic haplogroups allowing the tracing of different genetic branch points in human (and other organisms) evolution. Due to the large number of samples, it becomes necessary to automate the classification process. Using 5-fold cross-validation, we investigated two classification techniques on the consented database of 21 141 samples published by the Genographic project. The support vect...

ABCtoolbox: a versatile toolkit for approximate Bayesian computations

BMC Bioinformatics - Latest articles — Thu, 04 Mar 2010 00:00:00 +0100

Conclusion: ABCtoolbox allows a user to perform all the necessary steps of a full ABC analysis, from parameter sampling from prior distributions, data simulations, computation of summary statistics, estimation of posterior distributions, model choice, validation of the estimation procedure, and visualization of the results. (Source: BMC Bioinformatics - Latest articles)

AutoSOME: A clustering method for identifying gene expression modules without prior knowledge of cluster number

BMC Bioinformatics - Latest articles — Thu, 04 Mar 2010 00:00:00 +0100

Conclusions: By effectively extracting important information from high-dimensional microarray data without prior knowledge or the need for data filtration, AutoSOME can yield systems-level insights from whole genome microarray expression studies. Due to its generality, this new method should also have practical utility for a variety of data-intensive applications, including the results of deep sequencing experiments. AutoSOME is available for download at http://jimcooperlab.mcdb.ucsb.edu/autosome. (Source: BMC Bioinformatics - Latest articles)

Pathway-Based Feature Selection Algorithm for Cancer Microarray Data

Advances in Bioinformatics — Wed, 03 Mar 2010 16:46:41 +0100

Classification of cancers based on gene expressions produces better accuracy when compared to that of the clinical markers. Feature selection improves the accuracy of these classification algorithms by reducing the chance of overfitting that happens due to large number of features. We develop a new feature selection method called Biological Pathway-based Feature Selection (BPFS) for microarray data. Unlike most of the existing methods, our method integrates signaling and gene regulatory pathways with gene expression data to minimize the chance of overfitting of the method and to improve the test accuracy. Thus, BPFS selects a biologically meaningful feature set that is minimally redundant. Our experiments on published breast cancer datasets demonstrate that all of the top 20 genes found by...

MedWorm Message: Get the very latest Swine Flu news via the MedWorm Swine Flu RSS news feed - updated hourly from thousands of authoritative health and news sources.

Estimation of Cell Proliferation Dynamics Using CFSE Data.

Bulletin of Mathematical Biology — Wed, 03 Mar 2010 00:00:00 +0100

Authors: Banks HT, Sutton KL, Clayton Thompson W, Bocharov G, Roose D, Schenkel T, Meyerhans A Advances in fluorescent labeling of cells as measured by flow cytometry have allowed for quantitative studies of proliferating populations of cells. The investigations (Luzyanina et al. in J. Math. Biol. 54:57-89, 2007; J. Math. Biol., 2009; Theor. Biol. Med. Model. 4:1-26, 2007) contain a mathematical model with fluorescence intensity as a structure variable to describe the evolution in time of proliferating cells labeled by carboxyfluorescein succinimidyl ester (CFSE). Here, this model and several extensions/modifications are discussed. Suggestions for improvements are presented and analyzed with respect to statistical significance for better agreement between model solutions and experiment...

A State Space Transformation Can Yield Identifiable Models for Tracer Kinetic Studies with Enrichment Data.

Bulletin of Mathematical Biology — Wed, 03 Mar 2010 00:00:00 +0100

Authors: Ramakrishnan R, Ramakrishnan JD Tracer studies are analyzed almost universally by multicompartmental models where the state variables are tracer amounts or activities in the different pools. The model parameters are rate constants, defined naturally by expressing fluxes as fractions of the source pools. We consider an alternative state space with tracer enrichments or specific activities as the state variables, with the rate constants redefined by expressing fluxes as fractions of the destination pools. Although the redefinition may seem unphysiological, the commonly computed fractional synthetic rate actually expresses synthetic flux as a fraction of the product mass (destination pool). We show that, for a variety of structures, provided the structure is linear and stationary...

Conditions for Global Dynamic Stability of a Class of Resource-Bounded Model Ecosystems.

Bulletin of Mathematical Biology — Wed, 03 Mar 2010 00:00:00 +0100

Authors: Seymour RM, Knight G, Fung T This paper studies a class of dynamical systems that model multi-species ecosystems. These systems are 'resource bounded' in the sense that species compete to utilize an underlying limiting resource or substrate. This boundedness means that the relevant state space can be reduced to a simplex, with coordinates representing the proportions of substrate utilized by the various species. If the vector field is inward pointing on the boundary of the simplex, the state space is forward invariant under the system flow, a requirement that can be interpreted as the presence of non-zero exogenous recruitment. We consider conditions under which these model systems have a unique interior equilibrium that is globally asymptotically stable. The systems we consid...

Alterations in the red blood cell membrane proteome in alzheimer's subjects reflect disease-related changes and provide insight into altered cell morphology

Proteome Science — Wed, 03 Mar 2010 00:00:00 +0100

Conclusions: The results suggest that this study provides a potential link between the alterations in RBC membrane proteome in AD subjects and AD pathology. (Source: Proteome Science)

Impact of Missing Value Imputation on Classification for DNA Microarray Gene Expression Data—A Model-Based Study

EURASIP Journal on Bioinformatics and Systems Biology — Tue, 02 Mar 2010 17:48:20 +0100

Many missing-value (MV) imputation methods have been developed for microarray data, but only a few studies have investigated the relationship between MV imputation and classification accuracy. Furthermore, these studies are problematic in fundamental steps such as MV generation and classifier error estimation. In this work, we carry out a model-based study that addresses some of the issues in previous studies. Six popular imputation algorithms, two feature selection methods, and three classification rules are considered. The results suggest that it is beneficial to apply MV imputation when the noise level is high, variance is small, or gene-cluster correlation is strong, under small to moderate MV rates. In these cases, if data quality metrics are available, then it may be helpful to consi...

MedWorm Message: Get the very latest Swine Flu news via the MedWorm Swine Flu RSS news feed - updated hourly from thousands of authoritative health and news sources.

Confidence intervals that match Fisher's exact or Blaker's exact tests

Biostatistics — Tue, 02 Mar 2010 08:05:32 +0100

When analyzing a 2 x 2 table, the two-sided Fisher's exact test and the usual exact confidence interval (CI) for the odds ratio may give conflicting inferences; for example, the test rejects but the associated CI contains an odds ratio of 1. The problem is that the usual exact CI is the inversion of the test that rejects if either of the one-sided Fisher's exact tests rejects at half the nominal significance level. Further, the confidence set that is the inversion of the usual two-sided Fisher's exact test may not be an interval, so following Blaker (2000, Confidence curves and improved exact confidence intervals for discrete distributions. Canadian Journal of Statistics 28, 783–798), we define the "matching" interval as the smallest interval that contains the confidence set. We expl...

Bayesian inference for causal mediation effects using principal stratification with dichotomous mediators and outcomes

Biostatistics — Tue, 02 Mar 2010 08:05:32 +0100

Most investigations in the social and health sciences aim to understand the directional or causal relationship between a treatment or risk factor and outcome. Given the multitude of pathways through which the treatment or risk factor may affect the outcome, there is also an interest in decomposing the effect of a treatment of risk factor into "direct" and "mediated" effects. For example, child's socioeconomic status (risk factor) may have a direct effect on the risk of death (outcome) and an effect that may be mediated through the adulthood socioeconomic status (mediator). Building on the potential outcome framework for causal inference, we develop a Bayesian approach for estimating direct and mediated effects in the context of a dichotomous mediator and dichotomous outcome, which is chall...

Flexible Bayesian quantile regression for independent and clustered data

Biostatistics — Tue, 02 Mar 2010 08:05:32 +0100

Quantile regression has emerged as a useful supplement to ordinary mean regression. Traditional frequentist quantile regression makes very minimal assumptions on the form of the error distribution and thus is able to accommodate nonnormal errors, which are common in many applications. However, inference for these models is challenging, particularly for clustered or censored data. A Bayesian approach enables exact inference and is well suited to incorporate clustered, missing, or censored data. In this paper, we propose a flexible Bayesian quantile regression model. We assume that the error distribution is an infinite mixture of Gaussian densities subject to a stochastic constraint that enables inference on the quantile of interest. This method outperforms the traditional frequentist method...

Bayesian inference for finite mixtures of univariate and multivariate skew-normal and skew-t distributions

Biostatistics — Tue, 02 Mar 2010 08:05:32 +0100

Skew-normal and skew-t distributions have proved to be useful for capturing skewness and kurtosis in data directly without transformation. Recently, finite mixtures of such distributions have been considered as a more general tool for handling heterogeneous data involving asymmetric behaviors across subpopulations. We consider such mixture models for both univariate as well as multivariate data. This allows robust modeling of high-dimensional multimodal and asymmetric data generated by popular biotechnological platforms such as flow cytometry. We develop Bayesian inference based on data augmentation and Markov chain Monte Carlo (MCMC) sampling. In addition to the latent allocations, data augmentation is based on a stochastic representation of the skew-normal distribution in terms of a rand...

Estimating disease progression using panel data

Biostatistics — Tue, 02 Mar 2010 08:05:32 +0100

Continuous-time Markov processes are frequently used to describe the evolution of a disease over different phases. Such modeling can provide estimates for important parameters that are defined on the paths of the process. A simple example is the mean first hitting time to a set of states. However, more interesting events are defined by several time points such as the first time the process stays in state j for at least time units. These kinds of events are very important in relapsing–remitting diseases such as in multiple sclerosis (MS) where the focus is on a sustained worsening that lasts 6 months or longer. The current paper considers data on independent continuous Markov processes that are only observed intermittently. It reviews modeling and estimation, presents a new general co...

MedWorm Message: Get the very latest Swine Flu news via the MedWorm Swine Flu RSS news feed - updated hourly from thousands of authoritative health and news sources.

The competing risks illness-death model under cross-sectional sampling

Biostatistics — Tue, 02 Mar 2010 08:05:32 +0100

The competing risks illness–death model describes the dynamics of healthy subjects who may move to an "illness" state before entering into one of several competing terminal states. A motivating example concerns patients in a hospital who may acquire infections during their stay, where the competing terminal states are discharged alive and death in the hospital. We consider a cross-sectional sampling of independent competing risks illness–death processes in which data are subject to length bias and censoring and develop estimators for functionals of the underlying distribution such as the joint probability of the terminal state and illness (infection) and cumulative incidence functions. We apply the methodology to infection data obtained in a cross-sectional study of patients ho...

Bayesian ranking and selection methods using hierarchical mixture models in microarray studies

Biostatistics — Tue, 02 Mar 2010 08:05:32 +0100

The main purpose of microarray studies is screening to identify differentially expressed genes as candidates for further investigation. Because of limited resources in this stage, prioritizing or ranking genes is a relevant statistical task in microarray studies. In this article, we develop 3 empirical Bayes methods for gene ranking on the basis of differential expression, using hierarchical mixture models. These methods are based on (i) minimizing mean squared errors of estimation for parameters, (ii) minimizing mean squared errors of estimation for ranks of parameters, and (iii) maximizing sensitivity in selecting prespecified numbers of differential genes, with the largest effect. Our methods incorporate the mixture structures of differential and nondifferential components in empirical ...

A shifting level model algorithm that identifies aberrations in array-CGH data

Biostatistics — Tue, 02 Mar 2010 08:05:32 +0100

Array comparative genomic hybridization (aCGH) is a microarray technology that allows one to detect and map genomic alterations. The goal of aCGH analysis is to identify the boundaries of the regions where the number of DNA copies changes (breakpoint identification) and then to label each region as loss, neutral, or gain (calling). In this paper, we introduce a new algorithm, based on the shifting level model (SLM), with the aim of locating regions with different means of the log2 ratio in genomic profiles obtained from aCGH data. We combine the SLM algorithm with the CGHcall calling procedure and compare their performances with 5 state-of-the-art methods. When dealing with synthetic data, our method outperforms the other 5 algorithms in detecting the change in the number of DNA copies in ...

Robust depth-based tools for the analysis of gene expression data

Biostatistics — Tue, 02 Mar 2010 08:05:32 +0100

Microarray experiments provide data on the expression levels of thousands of genes and, therefore, statistical methods applicable to the analysis of such high-dimensional data are needed. In this paper, we propose robust nonparametric tools for the description and analysis of microarray data based on the concept of functional depth, which measures the centrality of an observation within a sample. We show that this concept can be easily adapted to high-dimensional observations and, in particular, to gene expression data. This allows the development of the following depth-based inference tools: (1) a scale curve for measuring and visualizing the dispersion of a set of points, (2) a rank test for deciding if 2 groups of multidimensional observations come from the same population, and (3) supe...

Frozen robust multiarray analysis (fRMA)

Biostatistics — Tue, 02 Mar 2010 08:05:32 +0100

Robust multiarray analysis (RMA) is the most widely used preprocessing algorithm for Affymetrix and Nimblegen gene expression microarrays. RMA performs background correction, normalization, and summarization in a modular way. The last 2 steps require multiple arrays to be analyzed simultaneously. The ability to borrow information across samples provides RMA various advantages. For example, the summarization step fits a parametric model that accounts for probe effects, assumed to be fixed across arrays, and improves outlier detection. Residuals, obtained from the fitted model, permit the creation of useful quality metrics. However, the dependence on multiple arrays has 2 drawbacks: (1) RMA cannot be used in clinical settings where samples must be processed individually or in small batches a...

MedWorm Message: Get the very latest Swine Flu news via the MedWorm Swine Flu RSS news feed - updated hourly from thousands of authoritative health and news sources.

Reconsidering the asymptotic null distribution of likelihood ratio tests for genetic linkage in multivariate variance components models under complete pleiotropy

Biostatistics — Tue, 02 Mar 2010 08:05:32 +0100

Accurate knowledge of the null distribution of hypothesis tests is important for valid application of the tests. In previous papers and software, the asymptotic null distribution of likelihood ratio tests for detecting genetic linkage in multivariate variance components models has been stated to be a mixture of chi-square distributions with binomial mixing probabilities. For variance components models under the complete pleiotropy assumption, we show by simulation and by theoretical arguments based on the geometry of the parameter space that all aspects of the previously stated asymptotic null distribution are incorrect—both the binomial mixing probabilities and the chi-square components. Correcting the null distribution gives more conservative critical values than previously stated,...

A doubly robust test for gene-environment interaction in family-based studies of affected offspring

Biostatistics — Tue, 02 Mar 2010 08:05:32 +0100

We develop a locally efficient test for (multiplicative) gene–environment interaction in family studies that collect genotypic information and environmental exposures for affected offspring along with genotypic information for their parents or relatives. The proposed test does not require modeling the effects of environmental exposures and is doubly robust in the sense of being valid if either a model for the main genetic effect holds or a model for the expected environmental exposure (given the offspring affection status and parental mating types) but not necessarily both. It extends the FBAT-I to allow for missing parental mating types and families of arbitrary size. Simulation studies and the analysis of an Alzheimer's disease study confirm the adequate performance of the proposed...

Boosting with missing predictors

Biostatistics — Tue, 02 Mar 2010 08:05:32 +0100

Boosting is an important tool in classification methodology. It combines the performance of many weak classifiers to produce a powerful committee, and its validity can be explained by additive modeling and maximum likelihood. The method has very general applications, especially for high-dimensional predictors. For example, it can be applied to distinguish cancer samples from healthy control samples by using antibody microarray data. Microarray data are often high-dimensional and many of them are incomplete. One natural idea is to impute a missing variable based on the observed predictors. However, the calculation of imputation for high-dimensional predictors with missing data may be rather tedious. In this paper, we propose 2 conditional mean imputation methods. They can be applied to the ...

Fast methods for spatially correlated multilevel functional data

Biostatistics — Tue, 02 Mar 2010 08:05:32 +0100

We propose a new methodological framework for the analysis of hierarchical functional data when the functions at the lowest level of the hierarchy are correlated. For small data sets, our methodology leads to a computational algorithm that is orders of magnitude more efficient than its closest competitor (seconds versus hours). For large data sets, our algorithm remains fast and has no current competitors. Thus, in contrast to published methods, we can now conduct routine simulations, leave-one-out analyses, and nonparametric bootstrap sampling. Our methods are inspired by and applied to data obtained from a state-of-the-art colon carcinogenesis scientific experiment. However, our models are general and will be relevant to many new data sets where the object of inference are functions or i...

Self-tolerance and Autoimmunity in a Regulatory T Cell Model.

Bulletin of Mathematical Biology — Tue, 02 Mar 2010 00:00:00 +0100

Authors: Alexander HK, Wahl LM The class of immunosuppressive lymphocytes known as regulatory T cells (Tregs) has been identified as a key component in preventing autoimmune diseases. Although Tregs have been incorporated previously in mathematical models of autoimmunity, we take a novel approach which emphasizes the importance of professional antigen presenting cells (pAPCs). We examine three possible mechanisms of Treg action (each in isolation) through ordinary differential equation (ODE) models. The immune response against a particular autoantigen is suppressed both by Tregs specific for that antigen and by Tregs of arbitrary specificities, through their action on either maturing or already mature pAPCs or on autoreactive effector T cells. In this deterministic approach, we find th...

MedWorm Message: Get the very latest Swine Flu news via the MedWorm Swine Flu RSS news feed - updated hourly from thousands of authoritative health and news sources.

OrgConv: detection of gene conversion using consensus sequences and its application in plant mitochondrial and chloroplast homologs

BMC Bioinformatics - Latest articles — Tue, 02 Mar 2010 00:00:00 +0100

Conclusions: Both the source code and the web interface of OrgConv are available for free from the OrgConv website (http://www.indiana.edu/~orgconv). Although OrgConv has been developed with main focus on detection of gene conversion between mitochondrial and chloroplast genes, it may also be used for detection of gene conversion between any two distinct groups of homologous sequences. (Source: BMC Bioinformatics - Latest articles)

Role of spiral wave pinning in inhomogeneous active media in the termination of atrial fibrillation by electrical cardioversion

Computers in Biology and Medicine — Mon, 01 Mar 2010 00:00:00 +0100

Abstract: Atrial fibrillation is the most common type of arrhythmia to affect humans. One of the treatment modalities for atrial fibrillation is an electrical cardioversion. Electrical cardioversion can result in one of three outcomes: an immediate termination of arrhythmic activity, a delayed termination or unsuccessful termination. The mechanism of delayed termination is unknown. Here we present a model of an atrial fibrillation as a coexistence of several spiral waves pinned to the inhomogeneities in active media. We show that in inhomogeneous system delayed termination can be explained as the unpinning of a spiral wave from inhomogeneities and its termination after collision with the edge of the system. (Source: Computers in Biology and Medicine)

The simulation of virus life cycle with quantum gates

Computers in Biology and Medicine — Mon, 01 Mar 2010 00:00:00 +0100

Abstract: Quantum physics and molecular biology are two disciplines that have evolved relatively independently. However, recently a wealth of evidence has demonstrated the importance of quantum mechanics for biological systems and thus a new field of quantum biology is emerging. There are many claims that quantum mechanics plays a key role in the origin and/or operation of biological organisms. We consider the nucleonic acid of virus as a quantum system in this paper and discuss virus life cycle from the view-point of quantum and simulate it using quantum gates for the first time. The maximally entangled states show infected cell can change to entire cell, the virus can switch from the lysogenic to the lytic and the prophages can remain latent in the bacterial chromosome for many generatio...

A user interface for VR-ready 3D medical imaging by off-the-shelf input devices

Computers in Biology and Medicine — Mon, 01 Mar 2010 00:00:00 +0100

Abstract: The distinctiveness of clinical environments demands specific solutions in the design of both usable and practical user interfaces for 3D medical imaging. In this work, a novel user interface to provide a direct interaction in 3D space by off-the-shelf input devices is proposed. The interface, which has been implemented and integrated into an open-source medical image viewer, features a depth-enhanced mouse pointer and a novel rotation technique that uses the object's geometry as the rotation handle. The usability of the proposed approach is evaluated to show its effectiveness for use in professional 3D imaging applications. (Source: Computers in Biology and Medicine)

Linked Metabolites: A tool for the construction of directed metabolic graphs

Computers in Biology and Medicine — Mon, 01 Mar 2010 00:00:00 +0100

Abstract: Metabolic pathway diagrams provide a wealth of information on how reactions combine to perform biological functions. While pathway diagrams are arranged in a way that allows a specific area of metabolism to be visualised, the inherent complexity of each pathway makes it difficult to identify the sets of reactions linking groups of compounds; a common task for researchers attempting to explain observed correlations or looking for further compounds of potential interest to use in validation work. Here we introduce Linked Metabolites, a tool that identifies sets of reactions linking groups of compounds in the context of the KEGG pathway diagrams. (Source: Computers in Biology and Medicine)

MedWorm Message: Get the very latest Swine Flu news via the MedWorm Swine Flu RSS news feed - updated hourly from thousands of authoritative health and news sources.

Automatic recognition of midline shift on brain CT images

Computers in Biology and Medicine — Mon, 01 Mar 2010 00:00:00 +0100

Abstract: Midline shift is one of the most important quantitative features clinicians use to evaluate the severity of brain compression by various pathologies. It can be recognized by modeling brain deformation according to the estimated biomechanical properties of the brain and the cerebrospinal fluid spaces. This paper proposes a novel method to identify the deformed midline according to the above hypothesis. In this model, the deformed midline is decomposed into three segments: the upper and the lower straight segments representing parts of the tough dura mater separating two brain hemispheres, and the central curved segment formed by a quadratic Bezier curve, representing the intervening soft brain tissue. The deformed midline is obtained by minimizing the summed square of the differen...

A methodology to identify consensus classes from clustering algorithms applied to immunohistochemical data from breast cancer patients

Computers in Biology and Medicine — Mon, 01 Mar 2010 00:00:00 +0100

Abstract: Single clustering methods have often been used to elucidate clusters in high dimensional medical data, even though reliance on a single algorithm is known to be problematic. In this paper, we present a methodology to determine a set of ‘core classes’ by using a range of techniques to reach consensus across several different clustering algorithms, and to ascertain the key characteristics of these classes. We apply the methodology to immunohistochemical data from breast cancer patients. In doing so, we identify six core classes, of which several may be novel sub-groups not previously emphasised in literature. (Source: Computers in Biology and Medicine)

A knowledge-driven probabilistic framework for the prediction of protein–protein interaction networks

Computers in Biology and Medicine — Mon, 01 Mar 2010 00:00:00 +0100

This study applied a knowledge-driven data integration framework for the inference of protein–protein interactions (PPI). Evidence from diverse genomic features is integrated using a knowledge-driven Bayesian network (KD-BN). Receiver operating characteristic (ROC) curves may not be the optimal assessment method to evaluate a classifier's performance in PPI prediction as the majority of the area under the curve (AUC) may not represent biologically meaningful results. It may be of benefit to interpret the AUC of a partial ROC curve whereby biologically interesting results are represented. Therefore, the novel application of the assessment method referred to as the partial ROC has been employed in this study to assess predictive performance of PPI predictions along with calculating the Tru...

Prediction of protein functions based on function–function correlation relations

Computers in Biology and Medicine — Mon, 01 Mar 2010 00:00:00 +0100

Abstract: A protein function pair approach, based on protein–protein interaction (PPI) data, is proposed to predict protein functions. Randomization tests are performed on the PPI dataset, which resulted in a protein function correlation scoring value which is used to rank the relative importance of a function pair. It has been found that certain classes of protein functions tend to be correlated together. Scoring values of these correlation pairs allow us to predict the functionality of a protein given that it interacts with proteins having well-defined function annotations.The jackknife test is used to validate the function pair method. The protein function pair approach achieves a prediction sensitivity comparable to an approach using more sophisticated method. The main advantages of ...

Relabeling algorithm for retrieval of noisy instances and improving prediction quality

Computers in Biology and Medicine — Mon, 01 Mar 2010 00:00:00 +0100

Abstract: A relabeling algorithm for retrieval of noisy instances with binary outcomes is presented. The relabeling algorithm iteratively retrieves, selects, and re-labels data instances (i.e., transforms a decision space) to improve prediction quality. It emphasizes knowledge generalization and confidence rather than classification accuracy. A confidence index incorporating classification accuracy, prediction error, impurities in the relabeled dataset, and cluster purities was designed. The proposed approach is illustrated with a binary outcome dataset and was successfully tested on the standard benchmark four UCI repository dataset as well as bladder cancer immunotherapy data. A subset of the most stable instances (i.e., 7% to 51% of the sample) with high confidence (i.e., between 64%–...

MedWorm Message: Get the very latest Swine Flu news via the MedWorm Swine Flu RSS news feed - updated hourly from thousands of authoritative health and news sources.

An image analysis pipeline for the semi-automated analysis of clinical fMRI images based on freely available software

Computers in Biology and Medicine — Mon, 01 Mar 2010 00:00:00 +0100

In this study, an efficient, semi-automated and cost-effective solution for the analysis of fMRI images acquired in a clinical setting is presented relying heavily on open source software. The core of the pipeline is the software Analysis of Functional NeuroImages (AFNI, National Institute of Mental Health (NIMH)) combined with K-PACS and ImageJ. Its application is illustrated with clinical fMRI exams and with a research study involving comparing subjects diagnosed with Parkinson's disease and age-matched controls. (Source: Computers in Biology and Medicine)

Three-dimensional thrombus segmentation in abdominal aortic aneurysms using graph search based on a triangular mesh

Computers in Biology and Medicine — Mon, 01 Mar 2010 00:00:00 +0100

Abstract: An abdominal aortic aneurysm (AAA) is the area of a localized widening of the abdominal aorta, with a frequent presence of thrombus. Segmentation and quantitative analysis of the thrombus in AAA are of paramount importance for diagnosis, risk assessment and determination of treatment options. The proposed thrombus segmentation method utilizes the power and flexibility of the 3-D graph search approach based on a triangular mesh. The method was tested in 9 3-D MDCT angiography data sets (9 patients with AAA, 1300 image slices), and the mean unsigned errors for the luminal and thrombotic surfaces were and . To achieve these results, control points needed to be interactively entered on image slices per 3-D CTA data set. (Source: Computers in Biology and Medicine)

Optimal therapeutic protocols in cancer immunotherapy

Computers in Biology and Medicine — Mon, 01 Mar 2010 00:00:00 +0100

Abstract: Using one of the well known mathematical models for immunotherapy of tumor–immune interactions, in this paper an algorithm is developed to optimize the immunotherapy in cancer treatment. The optimal control strategy is defined to maximize the effector cells and interleukin-2 concentration, while minimizing the tumor cells. The performance index is developed to stop the growth of tumor cells even at the end of the treatment. The maximum principle approach is the optimal control strategy in this paper. Analyzing the results and comparing them with very recent researches, it is shown that the amount of tumor cells with the proposed control algorithm is less then the others, both during and after the completion of the treatment. (Source: Computers in Biology and Medicine)

Computer validation and statistical correlations of a modern decompression diving algorithm

Computers in Biology and Medicine — Mon, 01 Mar 2010 00:00:00 +0100

Abstract: A diving algorithm is a safe combination of model and data to efficiently stage diver ascents following arbitrary underwater exposures. To that end, we detail a modern one, the LANL reduced gradient bubble model (RGBM), dynamical principles, and correlations with the LANL Data Bank data. Table, profile, and meter fit and risk parameters are obtained in statistical likelihood analysis from decompression exposure data. The RGBM algorithm enjoys extensive and utilitarian application in mixed gas diving, both in recreational and technical sectors, and forms the bases for released tables, software, and decompression meters used by scientific, commercial, and research divers. The LANL Data Bank is described, and the methods used to deduce risk are detailed. Risk functions for dissolved...

Breast-Cancer identification using HMM-fuzzy approach

Computers in Biology and Medicine — Mon, 01 Mar 2010 00:00:00 +0100

Abstract: This paper presents an ensemble of feature selection and classification technique for classifying two types of breast lesion, benign and malignant. Features are selected based on their area under the ROC curves (AUC) which are then classified using a hybrid hidden Markov model (HMM)-fuzzy approach. HMM generated log-likelihood values are used to generate minimized fuzzy rules which are further optimized using gradient descent algorithms in order to enhance classification performance. The developed model is applied to Wisconsin breast cancer dataset to test its performance. The results indicate that a combination of selected features and the HMM-fuzzy approach can classify effectively the lesion types using only two fuzzy rules. Our experimental results also indicate that the prop...

MedWorm Message: Get the very latest Swine Flu news via the MedWorm Swine Flu RSS news feed - updated hourly from thousands of authoritative health and news sources.

A tribute to Robert Steven Ledley

Computers in Biology and Medicine — Mon, 01 Mar 2010 00:00:00 +0100

As Computers in Biology and Medicine begins is fortieth year of publication, its Founding Editor, Robert Ledley, steps down as Editor-in-Chief. Pausing to consider this remarkable man and his accomplished career illuminates the histories of both the discipline of biomedical computing and of this journal, and may well provide insights into the forces that will shape both in future. The following comments are heavily indebted to the work of Joseph November, whose Ph.D. thesis for Princeton's Program in History of Science is serving as the basis of a new book about the early history of computers in biomedicine . November's work is a compelling (and fun) read for anyone working in this field, and documents the fragility of a new discipline and the careers of the people creating it—and the ma...

Editorial Board & Publication information

Computers in Biology and Medicine — Mon, 01 Mar 2010 00:00:00 +0100

(Source: Computers in Biology and Medicine)

The IronChip evaluation package: a package of perl modules for robust analysis of custom microarrays

BMC Bioinformatics - Latest articles — Mon, 01 Mar 2010 00:00:00 +0100

Conclusions: ICEP is a stand-alone Windows application to obtain optimal data quality from custom-designedmicroarrays and is freely available here (see "Additional Files" section) and at: http://www.alice-dsl.net/evgeniy.vainshtein/ICEP/ (Source: BMC Bioinformatics - Latest articles)

A novel method for sample preparation of fresh lung cancer tissue for proteomics analysis by tumor cell enrichment and removal of blood contaminants

Proteome Science — Fri, 26 Feb 2010 00:00:00 +0100

Conclusion: The method is feasible and reproducible. We could obtain a fair enrichment of cells but the major benefit of the method was an effective removal of contaminants from red blood cells and plasma proteins resulting in larger proteome coverage compared to the direct lysis of frozen samples. This sample preparation method may be successfully implemented for the discovery of lung cancer biomarkers on tissue samples using mass spectrometry-based proteomics. (Source: Proteome Science)

SplicerAV: A tool for mining microarray expression data for changes in RNA processing

BMC Bioinformatics - Latest articles — Thu, 25 Feb 2010 00:00:00 +0100

Conclusions: Using SplicerAV, we identified several hundred previously uncharacterized isoform changes induced by in vitro oncogene over-expression and revealed a previously unknown mechanism of EGFR activation in human mammary epithelial cells. We analyzed Affymetrix GeneChip data from over 400 human breast tumors in three independent studies, making this the largest clinical dataset analyzed for en masse changes in alternative mRNA processing. The capacity to detect RNA isoform changes in archival microarray data using SplicerAV allowed us to carry out the first analysis of isoform specific mRNA changes directly associated with cancer survival. (Source: BMC Bioinformatics - Latest articles)

MedWorm Message: Get the very latest Swine Flu news via the MedWorm Swine Flu RSS news feed - updated hourly from thousands of authoritative health and news sources.

Evolution and Diversity of the Human Hepatitis D Virus Genome

Advances in Bioinformatics — Wed, 24 Feb 2010 17:07:46 +0100

Human hepatitis delta virus (HDV) is the smallest RNA virus in genome. HDV genome is divided into a viroid-like sequence and a protein-coding sequence which could have originated from different resources and the HDV genome was eventually constituted through RNA recombination. The genome subsequently diversified through accumulation of mutations selected by interactions between the mutated RNA and proteins with host factors to successfully form the infectious virions. Therefore, we propose that the conservation of HDV nucleotide sequence is highly related with its functionality. Genome analysis of known HDV isolates shows that the C-terminal coding sequences of large delta antigen (LDAg) are the highest diversity than other regions of protein-coding sequences but they still retain biologica...

ProteinWorldDB: querying radical pairwise alignments among protein sets from complete genomes

Bioinformatics — Wed, 24 Feb 2010 12:48:52 +0100

Motivation: Many analyses in modern biological research are based on comparisons between biological sequences, resulting in functional, evolutionary and structural inferences. When large numbers of sequences are compared, heuristics are often used resulting in a certain lack of accuracy. In order to improve and validate results of such comparisons, we have performed radical all-against-all comparisons of 4 million protein sequences belonging to the RefSeq database, using an implementation of the Smith–Waterman algorithm. This extremely intensive computational approach was made possible with the help of World Community GridTM, through the Genome Comparison Project. The resulting database, ProteinWorldDB, which contains coordinates of pairwise protein alignments and their respective sc...

Xper2: introducing e-taxonomy

Bioinformatics — Wed, 24 Feb 2010 12:48:52 +0100

Motivation: Computer Aided Identification systems provide users with the resources to relate morpho-anatomic observations with taxa names and to subsequently access other knowledge about the organisms. They have the ability to manage descriptive data and make identifications through interactive keys. They are essential for both authors and users of biodiversity information. Xper2 version 2.0 is one of the most user-friendly tools in its category and provides a complete environment dedicated to taxonomic management. Availability: Xper2 software can be freely downloaded at http://lis-upmc.snv.jussieu.fr/lis/?q=en/resources/softwares/xper2 Contact: visotheary.riviere-ung@snv.jussieu.fr (Source: Bioinformatics)

dbTEU: a protein database of trace element utilization

Bioinformatics — Wed, 24 Feb 2010 12:48:51 +0100

We describe a database, dbTEU (DataBase of Trace Element Utilization), that features known transporters and user proteins for five trace elements (copper, molybdenum, nickel, cobalt and selenium) and represents sequenced organisms from the three domains of life. The manually curated dbTEU currently includes ~16 500 proteins from >700 organisms, and offers interactive trace element, protein, organism and sequence search and browse tools. Availability and Implementation: dbTEU is freely available at http://gladyshevlab.bwh.harvard.edu/trace_element/ Contact: vgladyshev@rics.bwh.harvard.edu (Source: Bioinformatics)

MSMSpdbb: providing protein databases of closely related organisms to improve proteomic characterization of prokaryotic microbes

Bioinformatics — Wed, 24 Feb 2010 12:48:51 +0100

Summary: The Microbial Proteomic Resource (MPR) is a repository service that contains non-redundant protein databases of related bacterial strains, which were generated through an in-house developed software called Multi-Strain Mass Spectrometry Prokaryotic DataBase Builder (MSMSpdbb). MSMSpdbb merges and clusters protein sequences inferred from genomic sequences, and provide a protein list in FASTA format that covers for divergence in gene annotation, translational start site choice and presence of single nucleotide polymorphisms and other mutations. Availability: MSMSpdbb was developed in C++ using the Qt libraries (Nokia) and licensed under the GNU General Public License version 2. MSMSpdbb is freely available, and its installation files, instructions for use and additional documentatio...

MedWorm Message: Get the very latest Swine Flu news via the MedWorm Swine Flu RSS news feed - updated hourly from thousands of authoritative health and news sources.

NEMO: a tool for analyzing gene and chromosome territory distributions from 3D-FISH experiments

Bioinformatics — Wed, 24 Feb 2010 12:48:51 +0100

Summary: Three-dimensional fluorescence in situ hybridization (3D-FISH) is used to study the organization and the positioning of chromosomes or specific sequences such as genes or RNA in cell nuclei. Many different programs (commercial or free) allow image analysis for 3D-FISH experiments. One of the more efficient open-source programs for automatically processing 3D-FISH microscopy images is Smart 3D-FISH, an ImageJ plug-in designed to automatically analyze distances between genes. One of the drawbacks of Smart 3D-FISH is that it has a rather basic user interface and produces its results in various text and image files thus making the data post-processing step time consuming. We developed a new Smart 3D-FISH graphical user interface, NEMO, which provides all information in the same place ...

Multifactor dimensionality reduction for graphics processing units enables genome-wide testing of epistasis in sporadic ALS

Bioinformatics — Wed, 24 Feb 2010 12:48:51 +0100

Motivation: Epistasis, the presence of gene–gene interactions, has been hypothesized to be at the root of many common human diseases, but current genome-wide association studies largely ignore its role. Multifactor dimensionality reduction (MDR) is a powerful model-free method for detecting epistatic relationships between genes, but computational costs have made its application to genome-wide data difficult. Graphics processing units (GPUs), the hardware responsible for rendering computer games, are powerful parallel processors. Using GPUs to run MDR on a genome-wide dataset allows for statistically rigorous testing of epistasis. Results: The implementation of MDR for GPUs (MDRGPU) includes core features of the widely used Java software package, MDR. This GPU implementation allows fo...

iDBPs: a web server for the identification of DNA binding proteins

Bioinformatics — Wed, 24 Feb 2010 12:48:51 +0100

Summary: The iDBPs server uses the three-dimensional (3D) structure of a query protein to predict whether it binds DNA. First, the algorithm predicts the functional region of the protein based on its evolutionary profile; the assumption is that large clusters of conserved residues are good markers of functional regions. Next, various characteristics of the predicted functional region as well as global features of the protein are calculated, such as the average surface electrostatic potential, the dipole moment and cluster-based amino acid conservation patterns. Finally, a random forests classifier is used to predict whether the query protein is likely to bind DNA and to estimate the prediction confidence. We have trained and tested the classifier on various datasets and shown that it outpe...

PyRosetta: a script-based interface for implementing molecular modeling algorithms using Rosetta

Bioinformatics — Wed, 24 Feb 2010 12:48:51 +0100

Summary: PyRosetta is a stand-alone Python-based implementation of the Rosetta molecular modeling package that allows users to write custom structure prediction and design algorithms using the major Rosetta sampling and scoring functions. PyRosetta contains Python bindings to libraries that define Rosetta functions including those for accessing and manipulating protein structure, calculating energies and running Monte Carlo-based simulations. PyRosetta can be used in two ways: (i) interactively, using iPython and (ii) script-based, using Python scripting. Interactive mode contains a number of help features and is ideal for beginners while script-mode is best suited for algorithm development. PyRosetta has similar computational performance to Rosetta, can be easily scaled up for cluster app...

PSiFR: an integrated resource for prediction of protein structure and function

Bioinformatics — Wed, 24 Feb 2010 12:48:51 +0100

Summary: In the post-genomic era, the annotation of protein function facilitates the understanding of various biological processes. To extend the range of function annotation methods to the twilight zone of sequence identity, we have developed approaches that exploit both protein tertiary structure and/or protein sequence evolutionary relationships. To serve the scientific community, we have integrated the structure prediction tools, TASSER, TASSER-Lite and METATASSER, and the functional inference tools, FINDSITE, a structure-based algorithm for binding site prediction, Gene Ontology molecular function inference and ligand screening, EFICAz2, a sequence-based approach to enzyme function inference and DBD-hunter, an algorithm for predicting DNA-binding proteins and associated DNA-binding re...

MedWorm Message: Get the very latest Swine Flu news via the MedWorm Swine Flu RSS news feed - updated hourly from thousands of authoritative health and news sources.

Next-generation bioinformatics: using many-core processor architecture to develop a web service for sequence alignment

Bioinformatics — Wed, 24 Feb 2010 12:48:51 +0100

Motivation: Bioinformatics algorithms and computing power are the main bottlenecks for analyzing huge amount of data generated by the current technologies, such as the ‘next-generation’ sequencing methodologies. At the same time, most powerful microprocessors are based on many-core chips, yet most applications cannot exploit such power, requiring parallelized algorithms. As an example of next-generation bioinformatics, we have developed from scratch a new parallelization of the Needleman–Wunsch (NW) sequence alignment algorithm for the 64-core Tile64 microprocessor. The unprecedented performance it offers for a standalone personal computer (PC) is discussed, optimally aligning sequences up to 20 times faster than the non-parallelized version, thus saving valuable time. Av...

CD-HIT Suite: a web server for clustering and comparing biological sequences

Bioinformatics — Wed, 24 Feb 2010 12:48:51 +0100

Summary: CD-HIT is a widely used program for clustering and comparing large biological sequence datasets. In order to further assist the CD-HIT users, we significantly improved this program with more functions and better accuracy, scalability and flexibility. Most importantly, we developed a new web server, CD-HIT Suite, for clustering a user-uploaded sequence dataset or comparing it to another dataset at different identity levels. Users can now interactively explore the clusters within web browsers. We also provide downloadable clusters for several public databases (NCBI NR, Swissprot and PDB) at different identity levels. Availability: Free access at http://cd-hit.org Contact: liwz@sdsc.edu Supplementary information: Supplementary data are available at Bioinformatics online. (Source: Bio...

rMAT - an R/Bioconductor package for analyzing ChIP-chip experiments

Bioinformatics — Wed, 24 Feb 2010 12:48:51 +0100

We present a fast, free and powerful, open source R package, rMAT, that allows the identification of regions enriched for transcription factor binding sites in ChIP-chip experiments on Affymetrix tiling arrays. Availability: The R-package rMAT is available from the Bioconductor web site at http://bioconductor.org and runs on Linux, MAC OS and MS-Windows. rMAT is distributed under the terms of the Artistic Licence 2.0. Contact: arnaud.droit@ircm.qc.ca; raphael.gottardo@ircm.qc.ca Supplementary information: Supplementary data are available at Bioinformatics online. (Source: Bioinformatics)

BamView: viewing mapped read alignment data in the context of the reference sequence

Bioinformatics — Wed, 24 Feb 2010 12:48:51 +0100

Summary: BamView is an interactive Java application for visualizing the large amounts of data stored for sequence reads which are aligned against a reference genome sequence. It supports the BAM (Binary Alignment/Map) format. It can be used in a number of contexts including SNP calling and structural annotation. BamView has also been integrated into Artemis so that the reads can be viewed in the context of the nucleotide sequence and genomic features. Availability: BamView and Artemis are freely available (under a GPL licence) for download (for MacOSX, UNIX and Windows) at: http://bamview.sourceforge.net/ Contact: artemis@sanger.ac.uk (Source: Bioinformatics)

Bayesian rule learning for biomedical data mining

Bioinformatics — Wed, 24 Feb 2010 12:48:51 +0100

This article describes an approach that uses a Bayesian score to evaluate rule models. Results: We have combined the expressiveness of rules with the mathematical rigor of Bayesian networks (BNs) to develop and evaluate a Bayesian rule learning (BRL) system. This system utilizes a novel variant of the K2 algorithm for building BNs from the training data to provide probabilistic scores for IF-antecedent-THEN-consequent rules using heuristic best-first search. We then apply rule-based inference to evaluate the learned models during 10-fold cross-validation performed two times. The BRL system is evaluated on 24 published ‘omic’ datasets, and on average it performs on par or better than other readily available rule learning methods. Moreover, BRL produces models that contain on ave...

MedWorm Message: Get the very latest Swine Flu news via the MedWorm Swine Flu RSS news feed - updated hourly from thousands of authoritative health and news sources.

Disambiguating the species of biomedical named entities using natural language parsers

Bioinformatics — Wed, 24 Feb 2010 12:48:51 +0100

This article reports on a comprehensive study on resolving the ambiguity in mentions of biomedical named entities with respect to model organisms and presents an array of approaches, with focus on methods utilizing natural language parsers. Results: We build a corpus for organism disambiguation where every occurrence of protein/gene entity is manually tagged with a species ID, and evaluate a number of methods on it. Promising results are obtained by training a machine learning model on syntactic parse trees, which is then used to decide whether an entity belongs to the model organism denoted by a neighbouring species-indicating word (e.g. yeast). The parser-based approaches are also compared with a supervised classification method and results indicate that the former are a more favorable c...

Computational quantification of metabolic fluxes from a single isotope snapshot: application to an animal biopsy

Bioinformatics — Wed, 24 Feb 2010 12:48:51 +0100

We report a novel analysis approach and software package for in vivo flux quantification using stable isotope labeling. Results: We developed a protocol based on brief, timed infusion of 13C isotope-enriched substrates for the tricarboxylic acid (TCA) cycle followed by quick freezing of tissue biopsies. NMR measurements of tissue extracts were used for flux estimation based on a computational model of carbon transitions between TCA cycle metabolites and related amino acids. To this end, we developed a computational framework in which metabolic systems can be flexibly assembled, simulated and analyzed. Flux parameters were quantified from NMR multiplets by a partial grid search followed by repeated Nelder–Mead optimizations implemented on a computer grid. We implemented a model of the...

Random distance dependent attachment as a model for neural network generation in the Caenorhabditis elegans

Bioinformatics — Wed, 24 Feb 2010 12:48:51 +0100

Motivation: The topology of the network induced by the neurons connectivity's in the Caenorhabditis elegans differs from most common random networks. The neurons positions of the C.elegans have been previously explained as being optimal to induce the required network wiring. We here propose a complementary explanation that the network wiring is the direct result of a local stochastic synapse formation process. Results: We show that a model based on the physical distance between neurons can explain the C.elegans neural network structure, specifically, we demonstrate that a simple model based on a geometrical synapse formation probability and the inhibition of short coherent cycles can explain the properties of the C.elegans' neural network. We suggest this model as an initial framework to d...

A censored beta mixture model for the estimation of the proportion of non-differentially expressed genes

Bioinformatics — Wed, 24 Feb 2010 12:48:51 +0100

Motivation: The proportion of non-differentially expressed genes (0) is an important quantity in microarray data analysis. Although many statistical methods have been proposed for its estimation, it is still necessary to develop more efficient methods. Methods: Our approach for improving 0 estimation is to modify an existing simple method by introducing artificial censoring to P-values. In a comprehensive simulation study and the applications to experimental datasets, we compare our method with eight existing estimation methods. Results: The simulation study confirms that our method can clearly improve the estimation performance. Compared with the existing methods, our method can generally provide a relatively accurate estimate with relatively small variance. Using experimental microarray ...

Faster computation of exact RNA shape probabilities

Bioinformatics — Wed, 24 Feb 2010 12:48:51 +0100

Conclusion: Evaluating this approach and several substrategies, we find that only a small proportion of shapes have to be actually computed. For an RNA sequence of length 400, this leads, depending on the threshold, to a 10–138 fold speed-up compared with the previous complete method. Thus, probabilistic shape analysis has become feasible in medium-scale applications, such as the screening of RNA transcripts in a bacterial genome. Availability: RapidShapes is available via http://bibiserv.cebitec.uni-bielefeld.de/rnashapes Contact: robert@techfak.uni-bielefeld.de Supplementary information: Supplementary data are available at Bioinformatics online. (Source: Bioinformatics)

MedWorm Message: Get the very latest Swine Flu news via the MedWorm Swine Flu RSS news feed - updated hourly from thousands of authoritative health and news sources.

Protein secondary structure appears to be robust under in silico evolution while protein disorder appears not to be

Bioinformatics — Wed, 24 Feb 2010 12:48:51 +0100

Motivation: The mutation of amino acids often impacts protein function and structure. Mutations without negative effect sustain evolutionary pressure. We study a particular aspect of structural robustness with respect to mutations: regular protein secondary structure and natively unstructured (intrinsically disordered) regions. Is the formation of regular secondary structure an intrinsic feature of amino acid sequences, or is it a feature that is lost upon mutation and is maintained by evolution against the odds? Similarly, is disorder an intrinsic sequence feature or is it difficult to maintain? To tackle these questions, we in silico mutated native protein sequences into random sequence-like ensembles and monitored the change in predicted secondary structure and disorder. Results: We est...

Active site prediction using evolutionary and structural information

Bioinformatics — Wed, 24 Feb 2010 12:48:51 +0100

Motivation: The identification of catalytic residues is a key step in understanding the function of enzymes. While a variety of computational methods have been developed for this task, accuracies have remained fairly low. The best existing method exploits information from sequence and structure to achieve a precision (the fraction of predicted catalytic residues that are catalytic) of 18.5% at a corresponding recall (the fraction of catalytic residues identified) of 57% on a standard benchmark. Here we present a new method, Discern, which provides a significant improvement over the state-of-the-art through the use of statistical techniques to derive a model with a small set of features that are jointly predictive of enzyme active sites. Results: In cross-validation experiments on two bench...

RNAsnoop: efficient target prediction for H/ACA snoRNAs

Bioinformatics — Wed, 24 Feb 2010 12:48:51 +0100

Motivation: Small nucleolar RNAs are an abundant class of non-coding RNAs that guide chemical modifications of rRNAs, snRNAs and some mRNAs. In the case of many ‘orphan’ snoRNAs, the targeted nucleotides remain unknown, however. The box H/ACA subclass determines uridine residues that are to be converted into pseudouridines via specific complementary binding in a well-defined secondary structure configuration that is outside the scope of common RNA (co-)folding algorithms. Results: RNAsnoop implements a dynamic programming algorithm that computes thermodynamically optimal H/ACA-RNA interactions in an efficient scanning variant. Complemented by an support vector machine (SVM)-based machine learning approach to distinguish true binding sites from spurious solutions and a system to...

Exploring classification strategies with the CoEPrA 2006 contest

Bioinformatics — Wed, 24 Feb 2010 12:48:50 +0100

Motivation: In silico methods to classify compounds as potential drugs that bind to a specific target become increasingly important for drug design. To build classification devices training sets of drugs with known activities are needed. For many such classification problems, not only qualitative but also quantitative information of a specific property (e.g. binding affinity) is available. The latter can be used to build a regression scheme to predict this property for new compounds. Predicting a compound property explicitly is generally more difficult than classifying that the property lies below or above a given threshold value. Hence, an indirect classification that is based on regression may lead to poorer results than a direct classification scheme. In fact, initially researchers are ...

Improving protein secondary structure prediction using a simple k-mer model

Bioinformatics — Wed, 24 Feb 2010 12:48:50 +0100

Motivation: Some first order methods for protein sequence analysis inherently treat each position as independent. We develop a general framework for introducing longer range interactions. We then demonstrate the power of our approach by applying it to secondary structure prediction; under the independence assumption, sequences produced by existing methods can produce features that are not protein like, an extreme example being a helix of length 1. Our goal was to make the predictions from state of the art methods more realistic, without loss of performance by other measures. Results: Our framework for longer range interactions is described as a k-mer order model. We succeeded in applying our model to the specific problem of secondary structure prediction, to be used as an additional layer ...

MedWorm Message: Get the very latest Swine Flu news via the MedWorm Swine Flu RSS news feed - updated hourly from thousands of authoritative health and news sources.

Fast and accurate long-read alignment with Burrows-Wheeler transform

Bioinformatics — Wed, 24 Feb 2010 12:48:50 +0100

Motivation: Many programs for aligning short sequencing reads to a reference genome have been developed in the last 2 years. Most of them are very efficient for short reads but inefficient or not applicable for reads >200 bp because the algorithms are heavily and specifically tuned for short queries with low sequencing error rate. However, some sequencing platforms already produce longer reads and others are expected to become available soon. For longer reads, hashing-based software such as BLAT and SSAHA2 remain the only choices. Nonetheless, these methods are substantially slower than short-read aligners in terms of aligned bases per unit time. Results: We designed and implemented a new algorithm, Burrows-Wheeler Aligner's Smith-Waterman Alignment (BWA-SW), to align long sequences up ...

Model of Active Transport of Ions Through Diatom Cell Biomembrane.

Bulletin of Mathematical Biology — Wed, 24 Feb 2010 00:00:00 +0100

Authors: Melkikh AV, Bessarab DS A model of the active transport of ions in the Cascinodiscus wailesii diatom cell is constructed taking into account the transport of H(+), Na(+), K(+), Ca(+2), [Formula: see text], Cl(-), and [Formula: see text] ions. This model allows calculating intracellular concentrations of basic ions and the biomembrane resting potential. A hierarchical algorithm "one ion-one transport system" is used in the model. The dependence of the resting potential on the extracellular concentration of potassium is plotted in terms of the model. The calculated values are in good agreement with the corresponding experimental data. PMID: 20180033 [PubMed - as supplied by publisher] (Source: Bulletin of Mathematical Biology)

Free energy estimation of short DNA duplex hybridizations

BMC Bioinformatics - Latest articles — Wed, 24 Feb 2010 00:00:00 +0100

Conclusions: Based on our preliminary results, we conclude that no statistically significant differences exist among free energy approximations obtained with 4 publicly available and widely used programs, when benchmarked against a collection of 695 pairs of short oligos collected and curated by the authors of this work based on 29 publications. The extended Nearest Neighbour model based on triplet interactions presented in this work is capable of performing accurate estimations of free energies for perfect match duplexes under both standard and non-standard experimental conditions and may serve as a baseline for further developments in this area of research. (Source: BMC Bioinformatics - Latest articles)

SpectraClassifier 1.0: a user friendly, automated MRS-based classifier-development system

BMC Bioinformatics - Latest articles — Wed, 24 Feb 2010 00:00:00 +0100

Conclusions: SC is a user-friendly software designed to fulfil the needs of potential users in the MRS community. It accepts all kinds of pre-processed MRS data types and classifies them semi-automatically, allowing spectroscopists to concentrate on interpretation of results with the use of its visualisation tools. (Source: BMC Bioinformatics - Latest articles)

Reconstructing genome trees of prokaryotes using overlapping genes

BMC Bioinformatics - Latest articles — Wed, 24 Feb 2010 00:00:00 +0100

Conclusions: In this study, we have introduced a new web server OGtree2 at http://bioalgorithm.life.nctu.edu.tw/OGtree2.0/ that can serve as a useful tool for reconstructing more precise and robust genome trees of prokaryotes according to their overlapping genes. (Source: BMC Bioinformatics - Latest articles)

MedWorm Message: Get the very latest Swine Flu news via the MedWorm Swine Flu RSS news feed - updated hourly from thousands of authoritative health and news sources.

Word add-in for ontology recognition: semantic enrichment of scientific literature

BMC Bioinformatics - Latest articles — Wed, 24 Feb 2010 00:00:00 +0100

Conclusions: The Word add-in for ontology term recognition makes it possible for an author to add semantic data to a document as it is being written and it encodes these data using XML tags that are effectively a standard in life sciences literature. Allowing authors to mark-up their own work will help increase the amount and quality of machine-readable literature metadata. (Source: BMC Bioinformatics - Latest articles)

Probe set filtering increases correlation between Affymetrix GeneChip and qRT-PCR expression measurements

BMC Bioinformatics - Latest articles — Wed, 24 Feb 2010 00:00:00 +0100

Conclusions: We show that filtering by fraction Present calls increased correlations for all 6 preprocessing algorithms. We observed the difference in performance of PM-MM and PM-only methods: using MM probes increased correlations in fold change studies, but PM-only methods proved to perform better in detection of differential expression. We recommend using GC-RMA for detection of differential expression and PLIER for estimation of fold change. The use of the more recent annotation improves the results in both types of studies, encouraging re-analysis of old data. (Source: BMC Bioinformatics - Latest articles)

Accurate and Scalable Techniques for the Complex/Pathway Membership Problem in Protein Networks

Advances in Bioinformatics — Tue, 23 Feb 2010 16:56:46 +0100

A protein network shows physical interactions as well as functional associations. An important usage of such networks is to discover unknown members of partially known complexes and pathways. A number of methods exist for such analyses, and they can be divided into two main categories based on their treatment of highly connected proteins. In this paper, we show that methods that are not affected by the degree (number of linkages) of a protein give more accurate predictions for certain complexes and pathways. We propose a network flow-based technique to compute the association probability of a pair of proteins. We extend the proposed technique using hierarchical clustering in order to scale well with the size of proteome. We also show that top-k queries are not suitable for a large number o...

An Intra-Host Mathematical Model on Interaction Between HIV and Malaria.

Bulletin of Mathematical Biology — Tue, 23 Feb 2010 00:00:00 +0100

Authors: Xiao D, Bossert WH In this paper a mathematical model is proposed for the interaction of the immune system with HIV viruses and malaria parasites in an individual host. It consists of a system of three coupled ordinary differential equations, which represents the rate of change in the concentration of malaria parasites, HIV viruses and immunity effector within a host, respectively. The theoretical model gives insight into the biological balance between pathogen replication and the immune response to the pathogen: persistence versus elimination of the pathogen, which determines the outcome of infection. Dynamical analysis shows that the outcomes of the interactions between the immune system of the host with either malaria parasites or HIV viruses are dramatic such as malaria in...

Extracting causal relations on HIV drug resistance from literature

BMC Bioinformatics - Latest articles — Tue, 23 Feb 2010 00:00:00 +0100

Conclusions: The proposed relation extraction and combination method has a good performance on extracting HIV drug resistance data. It can be used in large-scale relation extraction experiments. The developed methods can also be applied to extract other type of relations such as gene-protein, gene-disease, and disease-mutation. (Source: BMC Bioinformatics - Latest articles)

MedWorm Message: Get the very latest Swine Flu news via the MedWorm Swine Flu RSS news feed - updated hourly from thousands of authoritative health and news sources.

Development and implementation of a national telehealth project for long-term care: A preliminary study

Computer Methods and Programs in Biomedicine — Mon, 22 Feb 2010 16:58:08 +0100

Abstract: The aging population is a global phenomenon. The skyrocketing costs of healthcare and the shortage of healthcare providers will soon become a crucial issue all over the world. Taiwan's government executed the Taiwan's Telehealth Pilot Project (TTPP) from July 1, 2008 to December 31, 2008, using healthcare information technology to tackle these problems. The system has three different models, the home-care, the community-care, and the residential-care model to assist the elderly in the pursuit of better healthcare and improved quality of life. The results revealed both the home-care and community-care models facilitated timely medical responses if the enrolled patients had emergent conditions. In the home-care model, the hospital readmission rate was reduced from 8.19% to 3.17%, a...

A guideline-based decision support for pharmacological treatment can improve the quality of hyperlipidemia management

Computer Methods and Programs in Biomedicine — Mon, 22 Feb 2010 16:58:07 +0100

Conclusion: We conclude that a CPOE with CDSS integrated may let more hyperlipidemia patients reach the LDL-C goal. However, data also showed the total prescribing time may increase. The results of a preliminary evaluation are presented to illustrate that the CDSSs can improve the quality of hyperlipidemia management. (Source: Computer Methods and Programs in Biomedicine)

Saturn: A software application of tensor utilities for research in neuroimaging

Computer Methods and Programs in Biomedicine — Mon, 22 Feb 2010 16:58:07 +0100

We present an advanced software tool designed for visualization and quantitative analysis of Diffusion Tensor Imaging (DTI) called Saturn. The software is specially developed to help clinicians and researchers in neuroimaging, and includes a complete set of visualization capabilities to browse and analyze efficiently DTI data, making this application a powerful tool also for diagnosis purposes. The software includes a robust quantification method for DTI data, using an atlas-based method to automatically obtain equivalent anatomical fiber bundles and regions of interest among different DTI data sets. Consequently, a set of measurements is also implemented to perform robust group studies among subjects affected by neurological disorders and control groups in order to look for significant di...

Reducing blanking artifact in electrically evoked compound action potentials

Computer Methods and Programs in Biomedicine — Mon, 22 Feb 2010 16:58:07 +0100

Abstract: The main source of distortion in the recording of the electrically evoked compound action potentials is the stimulus artifact. The popular hardware blanking technique tends to reduce this artifact, but generates a blanking artifact as a consequence of the transient state in the amplifier. In this paper we propose two techniques to deal with the blanking artifact. The proposed techniques are combined with conventional and generalized alternating stimulation in order to reduce both stimulus and blanking artifacts in the recording of the evoked potentials. A comparison over 126 evoked potential recordings reveals that the proposed blanking artifact reduction methods improve the quality of electrically evoked compound action potential recordings. (Source: Computer Methods and Program...

Towards noise immune detection of fetal QRS complexes

Computer Methods and Programs in Biomedicine — Mon, 22 Feb 2010 16:58:07 +0100

In this study, we investigate the influence of different stages of fetal signals processing on the detection performance. The main propositions of the paper are: application of normalized matched filtering to fetal QRS complexes enhancement and a new approach to the final detection of the complexes. Compared to the classical detectors, the proposed new one allows a significant increase of the detection performance for signals of very different quality. (Source: Computer Methods and Programs in Biomedicine)

MedWorm Message: Get the very latest Swine Flu news via the MedWorm Swine Flu RSS news feed - updated hourly from thousands of authoritative health and news sources.

Development of subject-specific and statistical shape models of the knee using an efficient segmentation and mesh-morphing approach

Computer Methods and Programs in Biomedicine — Mon, 22 Feb 2010 16:58:07 +0100

Abstract: Subject-specific finite element models developed from imaging data provide functional representation of anatomical structures and have been used to evaluate healthy and pathologic knee mechanics. The creation of subject-specific models is a time-consuming process when considering manual segmentation and hexahedral (hex) meshing of the articular surfaces to ensure accurate contact assessment. Previous studies have emphasized automated mesh mapping to bone geometry from computed tomography (CT) scans, but have not considered cartilage and soft tissue structures. Statistical shape modeling has been proposed as an alternative approach to develop a population of subject models, but still requires manual segmentation and registration of a training set. Accordingly, the aim of the curre...

A semi-automatic algorithm for measurement of basement membrane thickness in kidneys in electron microscopy images

Computer Methods and Programs in Biomedicine — Mon, 22 Feb 2010 16:58:07 +0100

Abstract: In this paper, we present a semi-automatic algorithm for measurement of the glomerular basement membrane thickness in electron microscopy kidney images. A string of sparsely spaced points are manually inputted along the central line of the basement membrane (lamina densa) to be measured. The gaps between successive input points are lineally interpolated. A nonlinear mapping is applied to straighten the curved central line. Two distance functions of edges to the central line are constructed. The smooth envelope lines are obtained by repetitive applications of a linear low-pass filtering followed by a comparing and selecting process. The boundaries of the glomerular basement membrane are obtained from the inverse mapping of the envelope functions. The average basement membrane thic...

A simulation model of insulin saturation and glucose balance for glycemic control in ICU patients

Computer Methods and Programs in Biomedicine — Mon, 22 Feb 2010 16:58:07 +0100

Abstract: Consistent tight blood sugar control in critically ill patients has proven elusive. Properly accounting for the saturation of insulin action and reducing the need for frequent measurements are important aspects in intensive insulin therapy. This paper presents a composite metabolic model, ‘Glucosafe’, that integrates models and parameters from normal physiology and accounts for the reduced rate of glucose gut absorption and saturation of insulin action in patients with reduced insulin sensitivity. Particularly, two different sites of reduced insulin sensitivity, before and after the non-linearity of insulin action, are explored with this model. These approaches are assessed based on the model’s accuracy in retrospectively predicting blood glucose measurements of 10 randomly...

A framework for automatic construction of 3D PDM from segmented volumetric neuroradiological data sets

Computer Methods and Programs in Biomedicine — Mon, 22 Feb 2010 16:58:07 +0100

Abstract: 3D point distribution model (PDM) of subcortical structures can be applied in medical image analysis by providing priori-knowledge. However, accurate shape representation and point correspondence are still challenging for building 3D PDM. This paper presents a novel framework for the automated construction of 3D PDMs from a set of segmented volumetric images. First, a template shape is generated according to the spatial overlap. Then the corresponding landmarks among shapes are automatically identified by a novel hierarchical global-to-local approach, which combines iterative closest point based global registration and active surface model based local deformation to transform the template shape to all other shapes. Finally, a 3D PDM is constructed. Experiment results on four subc...

Editorial Board

Computer Methods and Programs in Biomedicine — Mon, 22 Feb 2010 16:58:07 +0100

(Source: Computer Methods and Programs in Biomedicine)

MedWorm Message: Get the very latest Swine Flu news via the MedWorm Swine Flu RSS news feed - updated hourly from thousands of authoritative health and news sources.

Preview of Python Testing Beginner’s Guide

Beginning Python for Bioinformatics — Mon, 22 Feb 2010 16:00:53 +0100

I was invited by Packt Publishing to review Python Testing Beginner’s Guide by Daniel Arbuckle. This is a book on one of the most important aspects of scientific programming (even though the majority of scientific software don’t have any testing routines): code testing, checking if your code actually does what is intended to do. I can say I’m not really an expert on testing so I guess I’m the right audience for it: You’ll learn about several of Python’s automated testing tools, and you’ll learn about the philosophies and methodologies that they were designed to support, like unit testing and test-driven development. When you’re done, you’ll be able to produce thoroughly tested code faster and more easily than ever before, and you’...

A reference guide for tree analysis and visualization

BioData Mining — Mon, 22 Feb 2010 00:00:00 +0100

In this study, we review tools that are currently available for the visualization of biological trees and analysis, mainly developed during the last decade. We describe the uniform and standard computer readable formats to represent tree hierarchies and we comment on the functionality and the limitations of these tools. We also discuss on how these tools can be developed further and should become integrated with various data sources. Here we focus on freely available software that offers to the users various tree-representation methodologies for biological data analysis. (Source: BioData Mining)

A new protein binding pocket similarity measure based on comparison of clouds of atoms in 3D: application to ligand prediction

BMC Bioinformatics - Latest articles — Mon, 22 Feb 2010 00:00:00 +0100

Conclusions: This study demonstrates the relevance of the proposed method to identify ligands binding to known binding pockets. We also provide a new benchmark for future work in this field. The new method and the benchmark are available athttp://cbio.ensmp.fr/paris (Source: BMC Bioinformatics - Latest articles)

DraGnET: Software for storing, managing and analyzing annotated draft genome sequence data

BMC Bioinformatics - Latest articles — Mon, 22 Feb 2010 00:00:00 +0100

Conclusions: DraGnET is designed for use either by individual researchers or as a collaborative tool available through Internet (or Intranet) deployment. For genome projects that require genome sequencing data to initially remain proprietary, DraGnET provides the means for researchers to keep their data in-house for analysis using local programs or until it is made publicly available, at which point it may be uploaded to additional analysis software applications. The DraGnET home page is available at http://www.dragnet.cvm.iastate.edu and includes example files for examining the functionalities, a link for downloading the DraGnET setup package and a link to the DraGnET source code hosted with full documentation on SourceForge. (Source: BMC Bioinformatics - Latest articles)

A robust numerical method for self-polarization energy of spherical quantum dots with finite confinement barriers.

Computer Physics Communications — Fri, 19 Feb 2010 09:40:06 +0100

Authors: Deng S By utilizing a novel three-layer dielectric model for the interface between a spherical quantum dot and the surrounding matrix, a robust numerical method for calculating the self-polarization energy of a spherical quantum dot with a finite confinement barrier is presented in this paper. The proposed numerical method can not only overcome the inherent mathematical divergence in the self-polarization energy which arises for the simplest and most widely used step-like model of the dielectric interface, but also completely eliminate the potential numerical divergence which may occur in the Bolcatto-Proetto's formula [J. Phys.: Condens. Matter 13, 319-334 (2001)], an approximation method commonly employed for more realistic three-layer dielectric models such as the linear an...

MedWorm Message: Get the very latest Swine Flu news via the MedWorm Swine Flu RSS news feed - updated hourly from thousands of authoritative health and news sources.

Preprocessing and downstream analysis of microarray DNA copy number profiles.

Briefings in Bioinformatics — Fri, 19 Feb 2010 00:00:00 +0100

Authors: van de Wiel MA, Picard F, van Wieringen WN, Ylstra B Analysis of DNA copy number profiles requires methods tailored to the specific nature of these data. The number of available data analysis methods has grown enormously in the last 5 years. We discuss the typical characteristics of DNA copy number data, as measured by microarray technology and review the extensive literature on preprocessing methods such as segmentation and calling. Subsequently, the focus narrows to applications of DNA copy number in cancer, in particular, several downstream analyses of multi-sample data sets such as testing, clustering and classification. Finally, we look ahead: what should we prepare for and which methodology-related topics may deserve attention in the near future? PMID: 20172948 [PubM...

A Model of CatSper Channel Mediated Calcium Dynamics in Mammalian Spermatozoa.

Bulletin of Mathematical Biology — Fri, 19 Feb 2010 00:00:00 +0100

Authors: Olson SD, Suarez SS, Fauci LJ CatSpers are calcium (Ca(2+)) channels that are located along the principal piece of mammalian sperm flagella and are directly linked to sperm motility and hyperactivation. It has been observed that Ca(2+) entry through CatSper channels triggers a tail to head Ca(2+) propagation in mouse sperm, as well as a sustained increase of Ca(2+) in the head. Here, we develop a mathematical model to investigate this propagation and sustained increase in the head. A 1-d reaction-diffusion model tracking intracellular Ca(2+) with flux terms for the CatSper channels, a leak flux, and plasma membrane Ca(2+) clearance mechanism is studied. Results of this simple model exhibit tail to head Ca(2+) propagation, but no sustained increase in the head. Therefore, in th...

Quasi-steady State Reduction of Molecular Motor-Based Models of Directed Intermittent Search.

Bulletin of Mathematical Biology — Fri, 19 Feb 2010 00:00:00 +0100

We present a quasi-steady state reduction of a linear reaction-hyperbolic master equation describing the directed intermittent search for a hidden target by a motor-driven particle moving on a one-dimensional filament track. The particle is injected at one end of the track and randomly switches between stationary search phases and mobile nonsearch phases that are biased in the anterograde direction. There is a finite possibility that the particle fails to find the target due to an absorbing boundary at the other end of the track. Such a scenario is exemplified by the motor-driven transport of vesicular cargo to synaptic targets located on the axon or dendrites of a neuron. The reduced model is described by a scalar Fokker-Planck (FP) equation, which has an additional inhomogeneous decay te...

Differential Geometry Based Multiscale Models.

Bulletin of Mathematical Biology — Fri, 19 Feb 2010 00:00:00 +0100

Authors: Wei GW Large chemical and biological systems such as fuel cells, ion channels, molecular motors, and viruses are of great importance to the scientific community and public health. Typically, these complex systems in conjunction with their aquatic environment pose a fabulous challenge to theoretical description, simulation, and prediction. In this work, we propose a differential geometry based multiscale paradigm to model complex macromolecular systems, and to put macroscopic and microscopic descriptions on an equal footing. In our approach, the differential geometry theory of surfaces and geometric measure theory are employed as a natural means to couple the macroscopic continuum mechanical description of the aquatic environment with the microscopic discrete atomistic descript...