MedWorm: Bioinformaticians

Tick-borne flaviviruses

VBRC Blog — Thu, 09 Oct 2008 21:29:34 +0100

Immunol Res. 2008 Oct 8. [Epub ahead of print] Tick-borne flaviviruses: dissecting host immune responses and virus countermeasures. read more (Source: VBRC Blog)

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The emergence of nipah virus

VBRC Blog — Thu, 09 Oct 2008 04:05:02 +0100

The emergence of Nipah virus, a highly pathogenic paramyxovirus. J Clin Virol. 2008 Oct 1; Authors: Lo MK, Rota PA read more (Source: VBRC Blog)

What is in a list of snp ? again, but a gui.

YOKOFAKUN — Thu, 09 Oct 2008 04:00:00 +0100

In a previous post I described how I generated some wrappers in java to map the tables of the mysql database at the UCSC, and I wrote a tool to get the data about a set of snp (cytoband, genes, hapmap...). Today I was asked if I could transform this application into a GUI (the fear of the infamous command line.. again...) That was straightforward to embed my code into an interactive software. I (Source: YOKOFAKUN)

Open source alternatives to endnote citation handling software

VBRC Blog — Wed, 08 Oct 2008 07:23:06 +0100

I was given the following list of free citation handling software: Are there any open source alternatives to EndNote? Yes. Most of the open source alternatives listed below are citation generators, which means they don’t store the citations for you, but they do automatically format them in a particular citation style after you’ve entered all the relevant information (author, title, etc.). A few others are markup languages, and one—Zotero—allows you to cite and store sources within your web browser. read more (Source: VBRC Blog)

Frameshifting and hidden genes

VBRC Blog — Wed, 08 Oct 2008 06:05:00 +0100

Ribosomal frameshifting and the world of hidden genes is mushrooming up in the field of bioinformatics! read more (Source: VBRC Blog)

Building a presentation with inkscape + batik. my notebook.

YOKOFAKUN — Wed, 08 Oct 2008 04:00:00 +0100

OK, I hate PowerPoint ... ... and I hate OpenOffice/Impress Next week, I'll present a talk about how to handle a bibliography with the tools available on the web (RSS, social bookmarking, zotero, etc...). Today I tried to build the slides using inkscape (the SVG editor) and apache batik (a Java-based toolkit for applications that want to use images in the SVG format). Each slide was drawn (Source: YOKOFAKUN)

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What is computational biology?

Trapped in the USA — Tue, 07 Oct 2008 22:35:19 +0100

I just submitted a manuscript to a computational biology journal, and during the process, I was asked how to classify it. Not being sure just exactly what computational biology is, it turns out that the website gave a handy little sub-categorization scheme for it, which clarified things immensely for me: Alternative Splicing Comparative Sequence Analysis Computational Neuroscience Ecosystem Modeling Genomics Literature Analysis Macromolecular Sequence Analysis Macromolecular Structure Analysis Metabolic Networks Metagenomics Molecular Dynamics Molecular Genetics Population Genetics Protein Homology Detection Protein Structure Prediction Sequence Motif Analysis Signaling Networks Synthetic Biology Systems Biology Transcriptional Regulation (Source: Trapped in the USA)

Canadian bioinformatics help desk

VBRC Blog — Tue, 07 Oct 2008 21:08:04 +0100

The Canadian Bioinformatics Help Desk is an endeavor by Genome Canada to unite a large number of Bioinformatics resources in one common forum. Among many useful features, the CBHD site hosts a directory of Bioinformatics researchers, a software repository and also a newsletter containing a software spotlight, job postings, and upcoming meeting read more (Source: VBRC Blog)

Estimates of poxvirus age

VBRC Blog — Tue, 07 Oct 2008 21:08:03 +0100

Genetika. 2008 Aug;44(8):1029-44. [Molecular evolution of poxviruses] [Article in Russian] [No authors listed] Previous restriction fragment length polymorphism analysis divided variola virus(VARV) strains into two subtypes, one of which included West Africanand South American isolates. This allowed a dating to be introduced for read more (Source: VBRC Blog)

Fosta - automatically extracting functionally equivalent proteins from swissprot

VBRC Blog — Tue, 07 Oct 2008 21:08:03 +0100

This month's issue of BMC Bioinformatics has seen the unveiling of FOSTA, a database and tool which provides access to a much needed library of Functionally Equivalent Proteins (FEPs). Excerpt from the Abstract (found here): read more (Source: VBRC Blog)

Bioinformatians ready?

VBRC Blog — Tue, 07 Oct 2008 21:08:03 +0100

Are we ready? read more (Source: VBRC Blog)

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Elucidating the human genes involved in west nile virus infection

VBRC Blog — Tue, 07 Oct 2008 21:08:02 +0100

A recent study published in Nature has made a significant step towards the mapping of those Human genes involved in the cellular propagation of West Nile virus. Through the use of RNA interference, 21,121 human genes were silenced and the effect on a WNV infection was monitored, yielding 305 host proteins that either positively or negatively affect viral synthesis. read more (Source: VBRC Blog)

Two journal special issues: big data, and semantic mashups for bioinformatics

Systems Biology & Bioinformatics — Tue, 07 Oct 2008 12:55:42 +0100

Both of these special issues are worth a look, as some of the papers look pretty interesting. I'll spend a little time in a later post on any articles I find particularly relevant. Semantic Mashup of Biomedical Data Special Issue of the Journal... Read and post comments | Send to a friend (Source: Systems Biology & Bioinformatics)

Birds [1]

Trapped in the USA — Mon, 06 Oct 2008 19:43:25 +0100

In every silk screen In every poster There are those same damn two birds Mother fucking birds There’s so many birds in the world Look, a fried chicken restaurant Let’s eat one and we will reduce the number of birds by one We can poop it out later ~ Zeecee Randall (Source: Trapped in the USA)

Birds

Trapped in the USA — Mon, 06 Oct 2008 05:52:14 +0100

Ignobels 2008

What You're Doing Is Rather Desperate — Sat, 04 Oct 2008 01:49:17 +0100

I mark the passing of the years in a couple of ways. One is natural events: the coral tree flowers in mid-winter, the jacaranda flowers in spring, the comings and goings of Queensland’s bird species. The other is the annual IgNobel award ceremony. 2008 is a vintage year: List of winners BBC News story The Guardian story It’s hard to choose a favourite this year. Armadillos and archaeology would have to be up there, but based on the idea that how much you laugh correlates with how much you relate, I’m going with: “You Bastard: A Narrative Exploration of the Experience of Indignation within Organizations”, from the journal Organization Studies. Posted in humour, publications, science news Tagged: 2008, ignobel (Source: What You're Doing Is Rather Desperate)

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Privacy survey

VBRC Blog — Fri, 03 Oct 2008 19:29:39 +0100

Jonathan Eisen over at the Tree of Life blog recently posted this blog. It seems that researchers are conducting an online survey about user's values surrounding privacy and are looking to get a few thousand people to complete the survey. This should take little of your time and you're helping websites tailor their policies to your needs and values :). read more (Source: VBRC Blog)

Java wrappers for the tables of the ucsc/goldenpath

YOKOFAKUN — Fri, 03 Oct 2008 04:00:00 +0100

Years ago, Jim Kent(UCSC) (the author of the BLAT algorithm) published in the Linux Journal "autoSql and autoXml: Code Generators from the Genome Project" the tools generate database definitions for SQL, write C header files with your data definitions and function prototypes, write C code to get data to and from C structures and generate C code for an XML parser. For example the following 'as' (Source: YOKOFAKUN)

Computational chemistry challenge: the power stroke of myosin that powers muscle contraction

Trapped in the USA — Thu, 02 Oct 2008 07:49:24 +0100

One of the most spectacular properties of proteins is that they can operate as motors. This is due to the unique property of a protein (as opposed to other polymers and small organic molecules) to spontaneously collapse into a very specific and very rigid 3-dimensional molecular arrangement for the protein. For the most part, proteins are rigid. However, there are flexible regions in the protein that allows the protein to undergo large rigid body motions that, when coupled with chemical reactions, result in a chemically driven motor. We know much about how about some of these motors work. For example, myosin is a motor that contracts our muscle cells. Myosin exists as little heads on a brushy fiber that spans the length of a muscle cell and this fiber is connected to the both ends of the muscle cell by a springy connector called titin. The myosin heads are stacked against two other pieces of fiber called actin that extends from either end of the cell. When there is the chemical fuel ATP flooding into the cell, the myosin heads will tug at the two pieces of actin. The cumulative tugging of thousands of myosin motors pulls the two pieces of actin towards the middle of the cell and the muscle cell is compressed. For a classical physicist, the vastly interesting question is how the myosin generates the force that tugs on the actin fiber. After the myosin latches on to the actin fiber, ATP naturally binds to the myosin in the special ATP binding site. When the phosphate breaks off the ATP, as ATP typically does, something mysterious happens that causes the whole back-end of the myosin to flip thus generating a huge mechanical kick (huge from the point of the myosin). It is this force that, when combined cumulatively with the forces from all the other myosin heads, pulls the two pieces of actin in the muscle cell together and compresses the cell. The molecular structure of myosin in different states are known, both in the ATP bound state (before the motor stroke), and in the ADP state (after the stroke when ATP has lost one of the phosphates). But we really don’t know what happens in between. From the analysis of the crystal structures, it appears that when the phosphate of the ATP breaks off, a long helix is shifted to cover the space where the phosphate used to be. As a result, the part of the protein at the end of the helix is forced to rotate by some 60º. Here’s a movie, based on static crystal structures, of how the motion might take place (that also includes some real-time Electron Microscopy images of the motion at the end of the movie): Beautiful optical trap experiments have been able to carefully tease apart individual myosin motors and thus measure the force generated by myosin, which is approximately 1-10 pN per motor, very small from our point of view, but enormous from the point of myosin. But where does the force come from? Understanding the details of this mechanical motion is, for me, one of the great challenges of computational chemistry. Is there some attraction of atoms to fill up the hole? Is there a cocked spring somewhere that releases the loaded helix? Is it some kind of subtle shift in an equilibrium ensemble – which will require a careful free-energy calculation? I see this challenge as computational because these kind of insights cannot be determined from experiment, the detail is too great. Where is the impasse in simulations? Given that the heart of the chemistry is a classical ATP hydrolysis, this problem will probably not need quantum mechanics – using molecular dynamics ought to be enough. Nevertheless, simulating these huge motions using vanilla molecular dynamics is many orders of magnitude greater than what can be achieved by current computational chemistry setups. Innovate methods of force generation using molecular dynamics protocols will be needed. (Source: Trapped in the USA)

Anti-obesity pills to fight viruses

VBRC Blog — Wed, 01 Oct 2008 22:38:18 +0100

As weird as it may sound, researchers have found a way to fight viruses using anti-obesity drugs. In a nutshell, they managed to target fatty acid biosynthesis in cells, preventing viruses from forming new envelopes. A review of the paper can be found on ScienceDaily, while the actual paper was published in Nature Biotechnology. read more (Source: VBRC Blog)

It would be too easy to rant and rave about this

What You're Doing Is Rather Desperate — Sat, 27 Sep 2008 02:15:58 +0100

Zotero is a marvellous, active open-source project, providing a Firefox extension that captures and formats bibliographic information from web pages. Thomson Reuters describe themselves as “the world’s leading source of intelligent information for businesses and professionals.” Whatever. They specialise in closed-source, proprietary solutions which to my simple mind is at odds with a role as an information source. Via FriendFeed from Rafael Sidi’s blog, I learn that Thomson Reuters are suing George Mason University, developers of Zotero, for “violating its license agreement and destroying the EndNote customer base”. Here’s my simple, black-and-white view of the world. The greatest achievement of the internet is the potential to set information free. There are free-thinking, forward-looking organisations like GMU who see this potential and act upon it. There are also organisations who see only threats to their corporate interests. Publishing corporations no longer control the flow of information to consumers and some of them seem to be struggling to accept this, adapt and move on. As I say, too easy to rant and rave. If you’d like to do so in the comments, feel free. Posted in bibliography, computing, zotero Tagged: george mason university, legal, thomson reuters (Source: What You're Doing Is Rather Desperate)

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Leave your mark on evolution with spore

VBRC Blog — Thu, 25 Sep 2008 21:29:11 +0100

Spore is a new educational tool, disguised as a game. It teaches kids the principles of evolution, natural selection, mutation and genetics in a fun way. Spore can be an excellent way to bring kids closer to biology, providing a base interest for the next Darwin. And hey, Spore is just a lot of fun for us too. Check it out. buisness|bytes|genes|molecules has a longer review if you are interested. read more (Source: VBRC Blog)

How to compute chemistry, conference report

Trapped in the USA — Thu, 25 Sep 2008 07:32:44 +0100

I kind of stumbled into my current field of research – molecular dynamics simulations of proteins – by accident and as a consequence, I never actively joined a particular community of researchers. I sometimes call myself a biophysicist but I am not really a physicist. But neither do I know a drop of chemistry. Whilst computational biology sounds like a great buzzword, it doesn’t really, well, mean anything. And nobody in my wet lab understands what I do, oh boo hoo. This all changed a couple of months ago when I went to my first Gordon Research Reference. As soon as I got on to the bus, I immediately got into a slanging match about atomic force fields. During the next 2 and a half hour bus ride, I argued with a bunch of strangers about thermodynamic ensembles, and integrators and dynamic protocls, and we hadn’t even started the meeting proper yet. And that’s when, suddenly, I realized: these are my folks. These strangers understood my problems, my bete noires, my pain. And we were all trying to get to the same place. These were computational chemists ergo I must be a computational chemist. I had come home. Based on that realization, during the meeting I started to take notice of the problems that concern computational chemists. What do chemists really want to simulate? Well, chemical reactions. For small molecules, you have to go full quantum, you must use all that heavy duty computation required to solve the Schrödinger equation or at least the density functional theory equation. But for reactions involving large macromolecules like protein and DNA, we can afford to approximate a little and use molecular dynamics to study interesting thermodynamic reactions such as protein folding, protein dynamics leading to allostery, large motor processes, and the effects of post-translational covalent modifications. Whilst many of us use molecular dynamics packages, we sometimes forget that they are fraught with foundational assumptions. Molecular Dynamics (MD) simulate molecules as if chemical bonds can never be broken or formed. Simple spring potentials model bond vibrations and a totally artificial r^(-12) term models intramolecular repulsion to stop atoms from forming new chemical bonds. Thus you can model a molecule like a chain of balls on a spring using good old Newtownian equations of motion. Furthermore, electrostatic interactions, which lead to complex electron exchange effects in quantum mechanics, are substituted with simple point charges in the center of every atom. But there are many ways to calculate how the electrostatic charges contribute to electrostatic effects including periodic fourier transforms and other fancy pants algorithms. I know that many of us computational chemists fancy ourselves as programmers and we all want to write their own MD package because well, we’d do so much better. But even a fraction of a moment’s sober thinking will bring one to the realization the impossibility of the task because if you are not actively developing a force field, or developing new numerical integration algorithms, then it’s just so much pissing in the wind. The hard part of writing an MD package is generating a good atomic force-field. Although each of the major MD packages implement their own force-fields, bits and pieces of each of them have infected each other. What we have is an eco-system atomic force-fields that are vaguely related to each other and no one really knows how they really differ. Still there are some brave souls trying to get past the standard MD atomic force fields. I am a personal fan of implicit solvent models where we pretend that water molecules don’t really exist and that they can be replaced with a surface tension term. Nathan Baker showed that there is still life in the old implicit solvent models yet, with some nice little twists on implicit solvent terms involving volume terms instead of surface tension, for instance. For those who come from physics, it’s common to see higher order approximations to complex equations solved, term by term. Given that static partial charges is a zero order approximation to electron density, a higher order approximation might be rotating dipoles. Except that polarizable terms – where rotating dipoles replace static charges – turn out to be a running joke in the conference. Another exciting approach to expanding molecular dynamics was Jana Khandogin’s constant pH simulations. Why is this exciting? Well, MD simulations typically forbid chemical bonds forming or breaking by fiat. But that’s essentially what happens to titratable amino acids at a constant pH. Hydrogens come on and off histidines, for instance. This of course can’t happen in molecular dynamics, and thus you never get to see dynamic changes involving pH effects. Constant pH simulations use a very elaborate chemical-alchemy approach to generate ghost hydrogen atoms, which actually do a pretty good job of approximating pH exchange effects. As you ramp up the pH – changing the population of free floating hydrogen atoms in the solvent – you get to see rather large changes in a protein conformation, which is what you’d expect to see according to experiments. But of course, the other big problem with MD simulations is that no one is really ever satisfied with how long the simulations run. Computational chemists are rather greedy in that regard. I came across various schemes to speed simulations up, including Andrew McCammon’s accelerated dynamics where you flatten potential wells to drive the simulations over the humps dynamically. Then there are all sorts of different ways to do replica-exchange and simulated annealing and every other bastard variation thereof. Of course these speeding up schemes would be utterly useless if there wasn’t a way to automagically smooth out the results so that the results of the simulation can “pretend” to have been simulated at a 300 K equilibrium using a normal MD simulation. Thank god for Jarzynski’s inequality and other such smoothing theorems that guarantee that you can transform a highly non-equilibrium ensemble into a canonical ensemble. There were many highly theoretical (re not very entertaining) talks that attempt to show that no matter how poorly sampled your simulation, you can still turn water into wine if you throw your results into the right wine-skin. There were quantum chemistry talks. I didn’t understand any of them except maybe for this neat talk that used QM/MD to reproduce some Electron Spin Resonance experiments. I was a bit chastened to see that there were few talks on coarse-grain model. My personal aesthetics is towards the simple so I feel like traitor somewhat in that now I do mostly MD simulations. The stand-out talk of the conference was a talk by Juan de Pablo, a materials statistical mechanics dude who presented superb coarse-grain simulations on DNA. Demonstrating the dictum that actual applications forces you to clarify your model, Juan showed some absolute awesome coarse-grain models of DNA spontaneously forming simple geometric patterns that helped him build nanoscale chips using simple thermodynamics. His models of simulating the process of inserting DNA inside a virus capsid were spell-binding. In contrast, we were forced to watch a whole series of multi-scale model talks, of which my response was, what’s the point? Supposedly, multi-scale models allows you to have a coarse model on the outside, and successively more details until you get to the high-level detail in the region of interest. It’s ugly as sin but if you can get the speed-up and consistent results then maybe it’s worth it. But unfortunately, you end up spending most of time dealing with the boundaries, and besides, there isn’t actually a serviceable problem to apply the method to. Everyone seems to do multi-scale models of water, but these models are stuck in no-man’s land. It’s not detailed enough to capture complex phase properties of water, not is it simple enough to allow a complete ensemble to be generated. So where’s the beef? Unfortunately, computational chemistry is not really at a stage where we can tackle really exciting protein reactions that involve conformational changes in large proteins. There were some isolated examples. Matt Jacobsen reported some preliminary long-time simulations of the phosphorylation of myosin in straight MD leading to large conformational changes. For large protein reactions still require some hand-tuned calculations. Alexei Stuchebrukhov used a custom fit electrostatic fitting protocol in a membrane potential to identify a plausible pathway for proton pumping in cytochrome C. Terry Lybrand showed some very subtle dynamic effects that affected selectivity of drugs between COX1 and COX2, two proteins that have virtually identical backbone structure. But really, the real action in this computational chemistry conference is ligand binding, by a country mile. This is where the money is. This is where the industry computational chemists live, eat and breathe. However, despite the sturm-and-drang of talk after talk of industry chemists detailing their new™ amazing™ much-improved™ ligand-binding software, the holy grail of a reliable calculation of ligand-binding affinities remains tantalizingly out of reach. If there is any more pressing theoretical problem for the pharmaceutical industry, I don’t know what it is. I will grant you that for certain class of ligands, poses can be predicted somewhat. But if you can’t have a reliable ligand-binding affinity then you really don’t know how well the ligand will actually work, like, as a drug. So it seems like the talks I saw were part of a merry-go-round of incremental improvements in predicting ligand-binding. Some have flexible backbones, some do not. Some have explicit waters some do not. Some fit charges, some do not. Some are fast, some are slow. Perhaps this is why the most exciting ligand binding talk essentially told everyone to STFU. Open Eyed Software has done the ligand-binding field a great service by organizing the CASP of ligand-binding. Called SAMPL, this was a proper blind test of the ligand-binding community. Even more difficult to organize than CASP, the organization of SAMPL required complex negotiations with various pharmaceuticals in order to get a test set for the competition. The results were at best, dissappointing, but disappoint in an entirely predictable kind of way. This is actually not so bad because if we take CASP as a guide, the first time CASP occurred, it was a real wet blanket as the whole community did really poorly. It took 2 more rounds before real progress was made. By then, I should be back at the Computational Chemistry Gordon Research Conference, hopefully whooping up in the highlands of Switzerland. (Source: Trapped in the USA)

Genomic analysis of pseudoalteromonas tunicata

What You're Doing Is Rather Desperate — Thu, 25 Sep 2008 06:31:41 +0100

Some years ago, I provided advice and a little analysis for a group at UNSW studying marine bacteria. It’s nice to see that they remembered me: Thomas, T., Evans, F.F., Schleheck, D., Mai-Prochnow, A., Burke, C., Penesyan, A., Dalisay, D.S., Stelzer-Braid, S., Saunders, N., Johnson, J., Ferriera, S., Kjelleberg, S. and Egan, S. (2008). Analysis of the Pseudoalteromonas tunicata Genome Reveals Properties of a Surface-Associated Life Style in the Marine Environment. PLoS ONE 3:e3252. If correlating genomic features with microbial physiology is your thing, go and check it out. The article is open access, for your pleasure - as are five of my last six efforts, I just noticed. Posted in bioinformatics, genomics, publications, research diary Tagged: plos one, pseudoalteromonas tunicata (Source: What You're Doing Is Rather Desperate)

Question: why does treasury need exactly $700 billion for bailout?

Trapped in the USA — Wed, 24 Sep 2008 23:57:20 +0100

Answer: “It’s not based on any particular data point,” a Treasury spokeswoman told Forbes.com Tuesday. “We just wanted to choose a really large number.” (Source: Trapped in the USA)

Theme change

What You're Doing Is Rather Desperate — Tue, 23 Sep 2008 06:02:29 +0100

Blog post about the blog - yawn! I’m trying a new, cleaner theme - The Journalist. It has one flaw - not at all obvious where to leave a comment. Answer: click on “with XX comments” (or “without comments”), above the post. Posted in this blog Tagged: design, themes (Source: What You're Doing Is Rather Desperate)

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I love spam!!!

Blind.Scientist — Sun, 21 Sep 2008 17:18:37 +0100

Just got a very interesting spam message: “Ex-hairdresser finds baldness cure among indians (native americans)”. I bet he is a molecular biologist now and found some genes related to baldness. It’s only downhill from here (Source: Blind.Scientist)

"oktapodi" - animated short

Trapped in the USA — Sat, 20 Sep 2008 19:33:08 +0100

oktapodi from inkman on Vimeo. (Source: Trapped in the USA)

Symba poster available for download

Systems Biology & Bioinformatics — Sat, 20 Sep 2008 06:06:10 +0100

The third-place-winning SyMBA poster (from the MGED 2008 Meeting) is now available for download for anyone interested. Enjoy! Read and post comments | Send to a friend (Source: Systems Biology & Bioinformatics)

Interfacial phenomena

business|bytes|genes|molecules — Sat, 20 Sep 2008 00:19:46 +0100

Zooming interfaces are cool. This week I have had a chance to see Zoomii in action, a Microsoft Surface, and of course, I use the multitouch zooming of the iphone quite regularly. In an interview with Jon Udell, Kristin Tolle, who works on biomedical computing at Microsoft Research had this to say Yeah, and we have these cool technologies. I think the WorldWide Telescope could be redeployed in many environments, and I think healthcare is one of those killer applications. We were talking with the National Cancer Institute, and one of the things they’d like to do is take a slice out of the liver while the patient is still on the table and be able to zoom in and zoom out — it’s the same technology. This was in response to a question on our abilities to make sense of complex data. I am very curious about how futuristic, or should we say modern since they’re here, will help our abilities to manipulate data, visualize it, etc. We have already seen the Google Maps API utilized to build genome browsers, and there is the stuff that Andrew has done. I have had the chance to see some very excellent visualizations, but they tend to have poor UIs and interaction models. That’s where I suspect we are going to see the most innovation in the coming years. Related articles by Zemanta Telling Stories on Maps (Source: business|bytes|genes|molecules)

Mia?

business|bytes|genes|molecules — Fri, 19 Sep 2008 12:10:25 +0100

No, contrary to popular belief no aliens are involved in my longest blog silence in a long time. Thanks to a hectic road trip, mostly at Web 2.0 Expo, haven’t had much of a chance to write about anything. In the meantime, the internet stayed up, the financial markets are in a mess, AWS made a huge announcement, and Tim O’Reilly gave a rather though provoking talk that I have to blog about soon. Oh, and the new Zemanta is sweet. Got a chance to meet Jure this week too :). Related articles by Zemanta O’Reilly: Stop throwing sheep, do something worthy (Caroline McCarthy/Webware.com) O’Reilly signals Free Web 2.0 party is over? (Source: business|bytes|genes|molecules)

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Center for the study of human polymorphisms: week 3

YOKOFAKUN — Fri, 19 Sep 2008 04:00:00 +0100

In my previous post I showed how I used apache velocity to generate some 'C' code for the Operon project based on BerkeleyDB. I also generated the Makefiles and some Lex and Yacc files to create a simple language to query each database. Today I've compiled and linked my first applications. Each application will use my simple language to query each database without having to write a new piece of (Source: YOKOFAKUN)

Genetic minitools - bioscripts.net

VBRC Blog — Fri, 19 Sep 2008 02:34:08 +0100

A number of biology-based resources have been pulled together on bioscripts.net. Although the vast majority of the site is written in Spanish, a number of very useful php-based tools can be found (in English) in the Biophp section. For any users who want to modify the tools, Francisco Galvez, the sites creator, has also provided the application source code. A small sample of these tools includes: DNA to protein translationPalindromic sequences finder read more (Source: VBRC Blog)

Not as many structures as you might think

What You're Doing Is Rather Desperate — Thu, 18 Sep 2008 05:14:26 +0100

In the midst of preparing a talk for next Monday. It occurred to me that perhaps we don’t see more protein structure-based prediction in bioinformatics because - there aren’t enough structures.pdbstatsSure, the PDB has grown a lot in the past 5 years or so and 53 103 structures (as of now) looks impressive. However, if you’re interested in protein-protein interaction, you want at least 2 chains: which more or less halves the dataset. If you want two different protein chains, you lose almost another 75%. Let’s specify a reasonable minimum resolution for X-ray diffraction data and there go ~ 3 000 entries. We probably don’t want multiple, similar proteins so let’s remove sequence identity at a redundancy of 90%. We’re left with about 2% of the original PDB, which might be useable for looking at interactions. No wonder that most bioinformatics focuses on sequences and high-throughput interaction data. (Source: What You're Doing Is Rather Desperate)

Great galloping gerbils!

Omics! Omics! — Thu, 18 Sep 2008 04:00:00 +0100

An item on CNN mentioned that satellite technology will be employed to monitor the endangered California Kangaroo Rat. This reminded me of a Nature paper this summer I meant to mention, because the image blew me away (plus it's the first time I've seen Google Earth used as a source for a scientific paper!).The paper is about models of disease spread (these gerbils are reservoirs for plague), but the thing which jumped out was the Google Earth image; the two images above are from around the same region of Kazakhstan. The gerbils clear vegetation from around their burrows, and these burrows are in huge complexes. The more zoomed in image above is several kilometers wide and yet is packed with gerbil burrows. If you have Google Earth and look around 44.766991 76.449699 you can zoom way out and still see the gerbil complexes. I saw some huge prairie dog towns out west when I was a boy, but nothing on this scale!How many animals leave traces which can be seen from 30+Km up (the image quality is uneven for this region of the world in Google Earth -- clearly shots are merged from different seasons and resolutions, but 30Km is a conservative estimate)? Human activity obviously. When I think of animal-built structures I generally jump to beaver dams or termite mounds, but they aren't nearly this extensive. (Source: Omics! Omics!)

Zillionformatics?

VBRC Blog — Thu, 18 Sep 2008 02:10:03 +0100

Generating c code with apache-velicity

YOKOFAKUN — Wed, 17 Sep 2008 04:00:00 +0100

I'm currently working on Operon ( http://regulon.cng.fr/) a database developped by Mario Foglio at The National Center of Genotyping. The whole database/storage is developped around the Berkeley C API and I've been asked to write a clean 'C' API to access the data. Most data are stored with C structures and I wanted to quickly write the methods to: * create a new instance of each structure * free (Source: YOKOFAKUN)

Web 2.0 meets socio-normative theory

Trapped in the USA — Wed, 17 Sep 2008 01:48:05 +0100

Where do you draw the line in the sand between the average joe and mr sick fuck? It’s a line that’s shifted in time from as far south as the Marquis de Sade to as far right as Queen Victoria. But where is it now? Worry no more because using fancy-pants Web 2.0 technology, budding sociologists with the help of the Internets can ask AmINormalOrNot.com? (Source: Trapped in the USA)

Dolphin birthing

Trapped in the USA — Tue, 16 Sep 2008 08:01:32 +0100

Some lucky photographer was outside the right tank at the right time somewhere in Italy, captured on film, for the first time ever, a dolphin giving birth. No yoga, or prenatal classes, or spiritual counseling – can you believe that? it just popped out. (Source: Trapped in the USA)

What is in a list of snp ?

YOKOFAKUN — Tue, 16 Sep 2008 04:00:00 +0100

Here is a common question: "Here is a list of snp genotyped with a high p-value. Is there anything interesting in this snp list ? is there a common link between those snp ?". Today, to answer this question, I've played with NCBI ELink. ELink checks for the existence of an external or Related Articles link from a list of one or more primary IDs; retrieves IDs and relevancy scores for links to (Source: YOKOFAKUN)

Industry watching: next generation biopharma

business|bytes|genes|molecules — Fri, 12 Sep 2008 13:00:47 +0100

We wonder whether the traditionally do-it-all, own-it-all from every part of the value chain is sustainable. It’s certainly a risky and costly model That quote comes from Elliot Sigal, the CSO at Bristol Myers-Squibb. Bio-IT World has an article where it talks about Sigal’s proposal to make BMS a next generation biopharma company. Hmmm, wonder what that means. As far as I can tell it means taking some of the blue sky research ethos of biotech and marrying it to the scale and commercial expertise of pharma and the ability to work in multiple therapeutic areas. Somehow I find that underwhelming, even distressing. Both are cliches to the core, and just words to a degree. What the industry needs is for people to think differently, not just talk about stuff that people talk about all the time. It is somewhat obvious that the industry needs to marry agility and innovation with the ability to bring products to market, but the models chosen are wrong. I don’t know for sure what the right answers are, but people need to look at where the innovation is happening, what the key needs are, and how they can be leveraged into successful therapeutics and sustainable pipelines. It must come through new models of collaboration and IP sharing between academia/non-profit and companies big and small. People should focus on their strengths and core competencies and not do too much. Where I agree with him is on focus and the following We actually set our discovery engine to less capacity than what we thought the whole organization needed so that we would force our portfolio strategy to go outside, level attrition, and to access innovation. What they also should force themselves to do is rethink that access layer. Related articles by Zemanta Bristol-Myers won’t raise ImClone offer Payday for biotech (Source: business|bytes|genes|molecules)

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Data friction

business|bytes|genes|molecules — Fri, 12 Sep 2008 00:41:46 +0100

it’s just striking how some very basic kinds of data friction keep getting in the way of ever-more-amazing possibilities for analysis and insight. – Jon Udell I don’t think I need to add anything to this line (at the end of a typically great post by Jon) I wonder what kind of data friction life scientists have to fight through. Back in the day, it was all the non-standard terms and slight changes that used to show up in the PDB. In recent times, I have heard of datasets (same kind of data) from different groups that had one column of different with no directions on what the different column meant. Try designing a schema for that. Of course, the need to come up with yet another data format is the favorite pastime of most life science data creators. Related articles by Zemanta The World Bank Opens API to Key Global Data (Source: business|bytes|genes|molecules)

Friends and feedy thoughts

business|bytes|genes|molecules — Wed, 10 Sep 2008 05:08:25 +0100

I hope Bret and co are paying attention. I’ve heard people say that Friendfeed is too noisy, that they don’t get the value, etc. The tech world has the unique ability to make anything too noisy and the worlds ultimate echo chamber. The scientific community on the other hand (life scientists, physicists, librarians and technologists) have made it a second home. We use it to discuss ideas and ask questions. Of course, every conference seems to get it’s own backchannel on Friendfeed, e.g. ISMB, BioBarCamp, Science in the 21st Century, Science Blogging 2008, etc. We even have rooms for programming and development efforts now, e.g.for Ruby for Python and for the Chemistry Development Kit. It’s a classic example of successful micro-communities, all coming together, driven by common interests. Makes you want to think ahead. Friendfeed has an API, a decent search engine, but what I would love to see is some way of mining all that data, cause in all the science rooms there is a ton of interesting information. I suspect you can do it today, just not sure what the best approach might be, and the graph of likes and comments and connections just HAS to be fascinating. Related articles by Zemanta Building scientific communities (Source: business|bytes|genes|molecules)

The uk e-science all hands meeting 2008

peanutbutter — Tue, 09 Sep 2008 10:34:41 +0100

Image via Wikipedia The UK e-science All Hands Meeting (AHM) 2008 is currently underway in Edinburgh. I will not be taking notes via this blog, instead I will be microblogging via my FriendFeed. Other delegates already on the FriendFeed band-wangon are Daniel Swan and Jean-Claude Bradly. Hopefully by the end we will have some more e-science FriendFeed converts. I will also be tagging AHM relevant posts via delicious using the tags e-science+AHM+ 2008. (Source: peanutbutter)

Your personal health: 23andme v2

business|bytes|genes|molecules — Tue, 09 Sep 2008 05:23:31 +0100

Image via CrunchBase, source unknown Did 23andme just cut prices? Update: Apparently they did A new blog post suggests that they’ve dropped prices to $399 (unless I am being completely dense and that’s an upsell). That information is part of the launch of 23andme v2. With the introduction of v2, our next-generation analytical platform, 23andMe customers will have access to an even more powerful set of the SNPs we use to probe their unique genetic composition. Can anyone with a 23andme account, or in the know, tell me what the potential and scope of the “analytical platform” is. I also suspect that v2 is on the 1M chip.. From the press release, it appears they are using the new Quad+ Beadchips The price reduction is largely made possible following technological advancements by Illumina — a leading provider of genetic analysis technologies — to its DNA Analysis Beadchips, which 23andMe uses to genotype customers. The new Beadchip, called the HumanHap550-Quad+, makes use of a four-sample format. 23andMe also has added improved custom content to the new Beadchip, which will include a broader range of Single Nucleotide Polymorphism (SNP) variations and rare mutations not found on the previous Beadchip, thereby providing more relevant data on published associations, as well as maternal and paternal ancestry. Need to dig into this more, but just saw the post and decided to throw it out there. Related articles by Zemanta Your SNPs are your information (Source: business|bytes|genes|molecules)

Collect, analyze, re-mix, re-purpose

business|bytes|genes|molecules — Tue, 09 Sep 2008 04:51:09 +0100

Image via Wikipedia Science was always about mashing up, taking one result and applying it to your [work] in a different way. The question is ‘Can we make that as effective [for] samples [of] data and analysis as it [is] for a map and set of addresses for a coffee shop?’ That is the vision. — Cameron Neylon Those words, found on a great post at the Science Commons blog, have been stuck in my head since I saw them. I’ve talked about mashing up science many times. In my time in the bioinformatics industry, the need to do “integrative genomics” comes up again and again, yet the approaches we adopt to solve those problems are either too heavy and complex, or simply abandoned due to the inherent gaps in our data. Mashups, e.g. the ones with Google Maps that we are all used to, are not trivial. They are enabled by some very cool technology at the back end, but we’ve managed to abstract away the complexity and enable creativity and utility. We need innovators in the life sciences, people who will build the backend infrastructure and enable creativity. The Biogang and many others in the community would be so much more effective given the right tools. We end up locking too much away in proprietary software, in complexity, or in paradigms written for a different era, but I think we’re making slow progress. Increasingly people are becoming aware of what can be achieved in today’s web-scale world. There are people who are at the cutting edge, but don’t quite look as cutting edge as they might have a few years ago. I would like to throw down the challenge to commercial providers of life science software. Join the web of data. Architect for innovation. Think about new business models, cause I am not sure the traditional ones are sustainable, and innovation is limited (with some notable exceptions). Help people not only collect and analyze data, but re-mix and re-purpose. (Source: business|bytes|genes|molecules)

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On parsing

What You're Doing Is Rather Desperate — Mon, 08 Sep 2008 06:09:44 +0100

Parsing - the act of ripping through a file, pulling out the relevant parts and doing something useful with them, is an integral part of bioinformatics. It can be a dull procedure. It can also be challenging, requiring creativity and imagination. Frequently as a bioinformatician, you will generate output from an unfamiliar program, or a colleague will bring you a file that you haven’t encountered. Your task is to figure out how the file is structured, which regular expressions are required to parse it, what kind of output to produce and most importantly, how to handle those rogue files which don’t obey the rules. Here’s my top ten (language-agnostic) parsing tips, focusing only on unstructured (non-XML) text files. Search for an existing parser… Most of us don’t have time to reinvent the wheel. First step: see if anyone else has solved the problem. The Bio* projects (bioperl, biopython, bioruby, biojava), for example, all include libraries to read and parse many common file formats: sequences, BLAST output and so on. There may be some effort involved in reading the documentation and learning to employ the methods, but it’s generally worth it. …but don’t trust it! On the other hand - don’t rely blindly on third-party code. You may find that there isn’t a method to do exactly what you want. Or there may be bugs, known or otherwise, in the library. Again, the solution is to know your library: search bug trackers, mailing lists and forums for known issues and submit any bugs that you find to the developers. Obtain a small sample output file Start with the smallest complete example output file that you can find. You don’t want to wait minutes/hours to test your code just because 1 GB of output is being read into memory. Examine the file contents Open up the file in an editor or even a pager and just have a good look at it. Where is the information that you want to extract? Is it in any way delimited: tabs, commas, spaces? Hint: on Linux, the command “hexdump -c filename | less” will show you delimiters and line endings. Is there anything unique about what you want to extract: all letters, all numbers, preceded by a colon? Can it occur zero, one or more than one times in the file? Start to jot down a few regular expressions. In the ideal case, your file format will have some kind of described schema. Example: the fasta sequence format, according to NCBI. Visualise the desired output Draw out a simple flowchart: inputs, processes, outputs, then figure out what your final output should look like. It may be something simple: “I want the sequence ID, sequence length, molecular mass and isoelectric point as comma-separated values”. Or more complex: you may want to pass the values on to a second procedure; generating an image, or updating a database table. In summary: figure out what you require from the input to get to the output. Simplify the file where possible It’s often the case that whilst a lot of a file consists of free, unstructured text, the relevant parts have some structure to them. An example would be the output from programs in the CCP4 package, which often contains space-delimited fields that describe protein chains, residues, atoms and interactions. Often, a file can be simplified using tools such as grep, awk and sed to extract the relevant lines. In fact, you may even find that these tools completely satisfy your parsing requirements. Design regular expressions Goes without saying really, but mastery of regular expressions in your language of choice is a real time saver. Imagine the exceptions This is perhaps the most difficult step in the procedure. It’s tempting to assume that all output from a given program will look the same, but there are multiple reasons why it may not; not least of which is human intervention between file generation and passing it on to you. So look at your code and ask: what if? What if the header line in a fasta sequence did not start with “>”? What if an amino acid residue is not one of the 20 standard 1-letter abbreviations? What if these fields were not separated by a space? If your code looks for a pattern, it should also fail gracefully and informatively should that pattern not be found. Here, I raise my hand to admit that this is an area in which I need to improve. Test, then scale up Get your code working on your small test file. Next, obtain more output files and try 10…then 50…then 100. Don’t get discouraged when your code (inevitably) breaks. Just make sure that you have a debugging procedure which at the very least, prints the name of the rogue file and if possible, the line number, so you can figure out quickly what’s gone wrong. Assuming (in Linux) that you have a directory named input full of input files, you can feed the first 10 to your script like so: for i in $(ls input | head -10); do my_script input/$i; done Make your parser reusable - by you and others Parsing a particular file type is almost certainly something you’ll need to do again and again, so make the code reusable. This means packaging it up as a class, module or whatever is applicable to the language. Better still - make it publicly available on the web, so as others can start at step (1) and build upon your work. (Source: What You're Doing Is Rather Desperate)

Self assembly: wikification

business|bytes|genes|molecules — Mon, 08 Sep 2008 00:00:32 +0100

Image via Wikipedia I love wikis. From the time I was exposed to them as part of software development efforts to Wikipedia (where I make little changes every now and them) and Citizendium, to more vertical wikis like EColiHub, the wiki has been a platform that has made a lot of sense for all kinds of activities. For Bioscreencast, the Bioscreencast Wiki has always been a key part of the site, as a general resource. An interest in Wikis as a collaborative platform was why a wiki was the most obvious platform for The Biogang. One of my goals for 2008 had been to move away from my current shared hosting to more virtualized hosting and development environments, which is why I got rid of my desktops, and am now using my macbook pro, a slice on Slicehost and Amazon Web Services (quite literally eating my own dogfood) as my computing/hosting environment. About half way there. In the past I had written about adopting Wikispaces as a wiki platform. I still love the platform, but things I wanted to do required hosting the wiki myself, and that led me to MindTouch Deki. It’s not quite your traditional wiki, but fits very well into what I want to use it for. That move coincided with the move to Slicehost, where the the bbgm wiki was the first thing that was set up. It’s taken a year to really get things to a point where the original idea makes sense, but slow and (not so) steady wins the race. The original germ came from Tantek Çelik’s Wiki. Over time I hope the bbgm wiki becomes its own resource, a place that contains some of the research and ideas behind the blog as well as various things I learn from attempts at doing some science and bad programming. The Deki platform has a RESTful API, so it can be used as more than just a content repository. Also the commenting functionality makes it possible to get feedback. If anyone is interested in contributing/editing/modifying, please let me know and I will add you as authors. I’ve also started funneling a feed of recent changes into Friendfeed. Next step - move bbgm to Slicehost and do more with deepaksingh.net>/a> Related articles by Zemanta Mememoir: A Better Wiki For Science Open Source Wiki, MindTouch “Deki Wiki”, is on ScobleShow today MindTouch Powers-Up DekiWiki with Dapper Larry Sanger says “tipping point” approaching for expert-guided Citizendium wiki (Source: business|bytes|genes|molecules)

Alternate views

business|bytes|genes|molecules — Sat, 06 Sep 2008 06:41:34 +0100

Just futzing around with Dipity. Here is an alternative to your normal list based RSS feed and fits in with the mood of the visualization theme earlier on Friendfeed Dipity first caught my attention due to its utilization of Freebase Related articles by Zemanta Dipity Do Da - An Interactive Collaborative Timeline To Track Wiki Contributions (Source: business|bytes|genes|molecules)

Mged by ally

peanutbutter — Fri, 05 Sep 2008 12:09:56 +0100

Ally has completed her comprehensive review of the 11th MGED Society meeting - I feel as if I was actually there. She also won 3rd place in the best poster competition which she presents SyMBA. (Source: peanutbutter)