Nodalpoint is back, as a podcast

If you read this blog than there is a very high chance that you know about Nodalpoint. It was one of the first (community) blogs related to science and where many bioinformatic bloggers, myself included, started out. Over the years, the site lost usage as people started their own independent blogs and Greg Tyrelle, the creator of Nodalpoint, eventually archived it.

The main website is back, in a way. Greg decided to start up a podcast series to discuss issues around bioinformatics and I guess whatever else he might be interested in. Go check it out. The first episode is a conversation with Neil Saunders, one of Nodalpoint's early users (blog, friendfeed, twitter) .

Among many other things, they talk about the lack of traction that open science has among scientists. I agree with some of the points that were raised regarding the small size niche of each specific research problem. It is not the full answer but it probably plays a role. There are so few people that have the skills and interest to tackle the same problem that creating a online community around any given scientific question becomes hard. Still, if we have not come together to openly share results and methods we have at least witness the creation of many online communities that are working very well to discuss all sort of different scientific issues  (ex. Friendfeed-Life Scientists, Biostart, Nature Network, etc).

Why do we blog?

Martin Fenner, asked some questions to science bloggers in Nature Networks that I think are interesting. Plus, the meme is going around my blogging neighbourhood so I thought I would join in as well:

1. What is your blog about?
It is mostly about science and technology with a particular focus on evolution, bioinformatics and the use of the web in science.

2. What will you never write about?
I will never blog about blog memes like this one. I tend to stay away from religion and politics but never is a very strong word.

3. Have you ever considered leaving science?
Does this mean academic research, research in general or science in general ? In any case no. I love problem solving and the freedom of academic research. The only thing I dislike about it is not being sure that I can keep doing this for as long as I wish.

4. What would you do instead?
If I could not do research I would probably try to work in scientific publishing. Doing research usually means that we have to focus on a very narrow field. Editors on the other hand are almost forced to broaden their scope and I think I would like this. I would also be interested in the use of new technologies in publishing.

5. What do you think will science blogging be like in 5 years?
Five years is a lot of time for the pace of technological development but not a long time for cultural change. I could be wrong but, if anything, there will be only a small increase in adoption of blogging as part of personal and group online presence along with the already existing web pages. I wish blogging (and other tools) would be use to further decentralize research agendas from physical location but I don't think that will happen in 5 years.

6. What is the most extraordinary thing that happened to you because of blogging?
I have gained a lot from blogging. The most concrete example was an invitation to attend SciFoo but there are many other things that are harder to evaluate. In some ways it is related to the benefits of attending conferences. It is useful because you get to interact with other scientists, exchange ideas, forces you to think through different perspectives, etc.

7. Did you write a blog post or comment you later regretted?
I probably did but I don't remember an example right now.

8. When did you first learn about science blogging?
As many other bioinformatic bloggers I started blogging in Nodalpoint, according to the archives in November 2001. I started this blog some two years after that.

9. What do your colleagues at work say about your blogging?
Not much really, I don't think many of them are aware of it. If any, the responses have been generally positive but I don't usually find many people interested in knowing more about blogging in science.

The biology of modular domains (day1 and morning of day2)

I am attending the 3rd (I think it is just the third) conference on modular protein domains. It is a small conference of just 80 people with a very nice environment for discussions. Given the nature of the conference I suspect that a lot of the talks will be about unpublished material so I will be light on the details since I have not personally asked people if I may post about their work.

In the first day of the conference on modular protein domains we had the opening lecture by Wendell Lim. It was a very light and interesting discussion of the evolution and engineering of signaling pathways. Lim started by discussing some interesting results coming from the sequencing of M. brevicollis, a unicellular choanoflagellate that is related to Metazoa and might provide some information about their evolution. It is a continuation of an analysis done by Nicole King and Sean B. Carroll that first identified a receptor tyrosine kinase in M. brevicollis, the first time one was identified outside of the Metazoa. The discussion was generally about the evolution of kinase signaling and how such a system of what Lim was naming "readers"~phospho-binding domains, "writers"~kinases and "erasers"~phosphotases can arise in evolution.
The second part of his talk was about the efforts to understand the evolutionary capacity of signaling networks by trying to engineer new or altered pathways. In this case the focus was on how with few components and small changes in these components it is possible to shape the dynamic responses of signaling networks.

Morning session of the second day

Synthetic biology
The Synthetic Biology sessions started off with a talk by David Searls on "A linguistic view of modularity in macromolecules and networks" (that was not very related to synthetic biology but nevertheless interesting). Searls detailed his views on the analogies between linguistics and biology. Here is a recent review by Mario Gimona on this analogy. At the protein level we could think of sequence, structure, function and protein role as similar to lexical, syntatic, semantic and pragmatic levels of linguistic analysis:

(Image reproduced with permission)

The general idea of building these bridges over topics is to be able to take existing methods and discussions from one side to the other (see review).

The second talk was by Kalle Saksela and again it had little to do with synthetic biology. Saksela's group is working on high-throughput interaction mapping for human SH3 domains against full proteins (human and viral proteins). They mentioned their progress in expressing and analyzing a subset of these interactions. He mentioned an interesting example were the Nck and Eps8L1 SH3 domain binding site in CD3epsilon overlaped with an ITAM motif such that the phosphorylation of the ITAM motif abolished binding by the SH3 domains. It is a nice example of signaling mediated by different types of peptide binding domains (see paper for details).

The third talk was by Rudolf Volkmer. He gave a short talk on a library of coiled coil proteins. The library contains many single mutant variants of the GCN4 leucine-zipper sequence. They then tested pairs mutants for heterodimerization by SPOT assays. Aside from a extending the knowledge of these domain family the library can also be used know as a toolkit of binding domains for synthetic biology (the work is already published).

The final talk on this panel was from Samantha Sutton from the Drew Endy lab. This was more like what one would expect from a synthetic biology talk . Samantha Sutton is interested in developing what she calls Post Translational Devices, general abstract devices that can regulate the post translational state of proteins in a predictable fashion. She has a page in OpenWetWare detailing her thoughts on this.

The second panel in the morning was about In silico computational methods.
Cesareni presented their ongoing efforts to experimentally determine human SH3 and SH2 interactions with spotted peptides. He then showed how this data can be used to search for examples where there is overlapping recognition by different domain types. The work is similar in methodology to the paper published by Christiane Landgraf and colleagues in PLoS Biology but know using two domain families and the human proteome.

Vernon Alvarez from AxCell Biosciences, gave a talk about a proprietary database called ProChart (that I cannot find online) containing many domain-peptide interactions tested by the company. He was basically promoting the database for anyone interested in collaborations.

The third talk was by Norman Davey author of SLIMDisc a linear motif discovery method. He is trying to improve their method, mostly by improving the statistics.

I gave the second short talk of the session. It was on predicting binding specificity of peptide binding domains using structural information. It is basically a continuation of some of the work I mentioned before here in the blog about the use of structures in systems biology but know applied to domain-peptide interactions.

BioBlogs #12 and a blogroll update

The 12th edition of Bio::Blogs is out in Nodalpoint. It has been one year of monthly posts (mostly) about bioinformatics. Is anyone interested in hosting the next edition ?

Also, I updated my blogroll to reflect more what I am currently reading. Most updates are in the bioinformatics part but there are a couple of additions in all of them.

Presenting Blog Citations

Recently Postgenomic hit the 10k mark. Ten thousand citations to papers and books have been tracked in science related blogs. In the post announcing the milestone, Euan asked if blog buzz could be an indication of impact of a paper. Can science bloggers help to highlight potentially interesting research ?

I decided to have a look at this and asked him to send in a list of papers published in 2003-2004 and mentioned in blog posts. For these I took from ISI Web of Science the number of citations in papers tracked by ISI (all years). There are 519 papers published in 170 journals in the period of 2003-2004 that were mentioned in blogs tracked by Postgenomic. Of these, 79 papers could not be found in ISI. Many of the papers not found in ISI were published in arXiv. These 79 were no longer considered for further analysis.

Top cited journals in blog posts

I ranked the journals according to the incoming blog citations. The top 5 are highlighted below, and apart from arXiv, that is not usually tracked as a journal (maybe it should), the other 4 are all known journals publishing in general science/biology. Comparing to impact factors there is a noted absence of review and medical journals. This measure of blog citations (instead of blog citations per article) will penalize low volume journals like the Annual Review series. Regarding the low blog impact of medical journals, maybe the current journal ranking by blog citations reflects a higher proportion of biology and physics blogs currently tracked by postgenomic.


Relation between blog citations and average literature citations

The fact the bloggers tend to cite research published in high-impact journals could be just due to the higher visibility of these journals. To test this, I analyzed the average citation per article from papers published in 2003-2004 in any journal with more than 1,2 and 3 blog citations (see table below). I compared it to papers published in Science and Nature in the same period. It is possible to conclude that: 1) papers mentioned in blogs have a higher average citation than those published in these high impact journals: 2) papers with increasing blog citations have on average a higher number of literature citations.

Journal	Papers in 2003-2004	Citations	Average citation per paper
Science	5306	148912	28.06
Nature	5193	145478	28.01
>0 blog citations	440	21306	48.42
>1 blog citations	71	3679	51.81
>2 blog citations	24	1835	76.45
>3 blog citations	15	1557	103.8

I did not remove non-citable items (editorials, news and view, letters, etc) from the analysis. It would hard to come up with criteria for removing these from both the journals and from the papers tracked by postgenomic. In any case, I suspect that bloggers tend to blog a lot about of non-citable items because these are usually more engaging for discussions than research papers. Therefore if anything I suspect that the real measure of impact for blog cited items should be even higher.

Our global distributed journal club

In recent years science publishers have worked to adjust to publishing online. Most of them now offer RSS feeds for their content and some timidly started allowing readers to comment on their sites. With the exception of BioMed Central none of the publishers make of point of prominently showing these comments, making it harder to find out about interesting ongoing discussions. This has not stopped researchers from participating on what can be called a global distributed journal club. As Euan and others have nicely noted, scientists are using blogs to discuss research. It is a very diffuse discussion but it can be aggregated in way that it could never be possible if we kept to ourselves, in the usual conferences or in our institutes/universities.

I tried to show here that this aggregated discussion conveys information regarding the potential impact of published research. This is only the tip of the iceberg of the potential benefits of aggregating and analyzing science blogs. For example, it should be possible to look for related papers from the linking patterns of science bloggers; the dynamics of communication between different science disciplines; the trends in technology development, etc.

Some publishers might be thinking of ways to reproduce these discussions in their sites. One alternative would be for science publishers to get together in the development of the aggregation technology. There should be an independent site gathering all the ongoing comments from blog posts and from the publishers' websites. This could then be used by anyone interested in the information. It could be shown next to a pubmed abstract or directly in the publishers website. Right now this would likely be the single biggest incentive to online science discussions that science publishers could do.

Its official ;), scientists enter the blogoshere

Laura Bonetta wrote an analysis piece in Cell about scientists entering the blogosphere. Laura Bonetta (could not find her blog :) does a god job of introducing science blogging in a short and easy to read assay. There is a bit of everything: science education, discussions, carnivals and open science. The only thing that is sorely lacking is a mention of Postgenomic and maybe the publishers blogs.

The publisher's reaction

Sarah Cooney, Director of Publications for the Society of Chemical Industry as issued an official reply to the gathering criticism:

"We apologise for any misunderstanding. In this situation the publisher would typically grant permission on request in order to ensure that figures and extracts are properly credited. We do not think there is any need to pursue this matter further."

The email was posted in Shelley Batts blog and also in this blog post at Nature Network. Overall it is good news, this was an honest mistake and not a policy from the journal nor the publisher. There is a hint in the official reply to some potentially abusive emails sent to the editor. Maybe, as Euan Adie suggested this is also a lesson for science bloggers to take care of rising mob mentality when handling these issues. I would guess that many editors might not even be aware of their own copyright/fair use policies and this issue might at least raise the discussion.

How can a publisher be so dumb - Update

I posted a while ago about copyright policies of different science publishers regarding images. I concluded by saying that in any case we should be safe to blog images since no publisher would likely sue a blogger for using an image or two to promote one of their papers. Well ... apparently I was wrong. Shelley Batts from Retrospectable got an email from an editor of the Journal of the Science of Food and Agriculture (published by Wiley Interscience):

"The above article contains copyrighted material in the form of a table and graphs taken from a recently published paper in the Journal of the Science of Food and Agriculture. If these figures are not removed immediately, lawyers from John Wiley & Sons will contact you with further action."

This is not a legal action but the threat is there. I cannot see what they were thinking. Are they really willing to sue a blogger for what is very likely fair use of their content? The content used is a small fraction of the whole, the blog post is educational and most likely has increased the traffic to that paper. If anything this email just bought them a lot of indignation and it will be a PR nightmare for the journal and the publisher.

Science bloggers are doing a great service of covering science news, faster and more in depth than most traditional news services. Every time I have a look these days at the first page of Postgenomic I see there what is going to be the main science stories of the next day in the normal news outlets. Not only that but I will likely find someone that actually works on the subject and can give a very good explanation of what the work is about. Publishers should be fostering this by crafting policies directed at this use of their material not the other way around.

If you want to contact the editor that made the decision the email is on Shelley's post.

There is a large number of posts reacting to this in Postgenomic.

Update - Boing Boing is giving coverage to this too. If you also think that this was a bad decision from the journal editor/publisher consider writing about it or sending them an email. Even if it is within their legal right to do so we can at least tell them that we don't find this appropriate or fair.

Cellular adaptation to unforeseeable events

How do cells react to changes in external conditions ? It has been noted before than in many cases the immediate transcriptional response includes unspecific changes in gene expression for a large group of genes (Gash et al, 2000). Fong and colleagues have shown that in E. coli, 20 to 40 days after the initial changes, most of the genes return to expression levels prior to the modifications of the environment. The differentially expressed genes at this stage are situation specific but not necessarily always the same. In this same paper, the gene expression changes were followed for different independent populations evolving under the same changes in conditions. Out of ~1100 gene expression changes (on average) that were possibly adaptive to the new conditions, only 70 were common to all 7 parallel populations.

A new studied published in MSB, adds more information to these interesting findings. In this study the authors tried to challenge S. cerevisiae with a perturbation that these cells should not have seen during their evolutionary history. They used a his3 deletion strain with a plasmid having HIS3 under the GAL1 promoter. In these cells the essential HIS3 gene should be efficiently turned off in a glucose medium. They then tracked the gene expression changes over time when the medium was changed from galactose to glucose. The cells adapted to these conditions within around 10-20 generations. Again the initial gene expression changes involved a large number of genes (~1000-1600 genes> 2 fold change) with most of them (65%-70% ) returning to their original expression levels in 10-20 generations. Again, different populations had different genes differentially expressed in response to the transition from gal to glu.

There is a detailed analysis in the paper regarding the functional classes of the genes but for me these general trends were by themselves very interesting. How does the cell cope with unforeseeable events ?

Maybe there is a general mechanism that senses discrepancies between metabolic requirements and the current cellular state and, in the absence of a programed response, drives an almost chaotic search for plausible solutions ? If there is such a sensing mechanism it could provide the necessary feedback for the selection of cellular states at a physiological time scale. In a environment were frequent unpredictable changes occur such a system could possibly be selected for.

For further reading have a look at the news and views by Eugene Koonin

The Seven Stones blog and more quick links

The Nature family of blogs as a new member - The Seven Stones - from the Molecular Systems Biology journal. I gave some help to set it up during my 3 months stay with the journal. Go over there and say hello to the editors :).

(via Deepak) The TED.com site was relaunched. It is has one of the most amazing collection of video talks available. The current main focus is The Rise of Collaboration.

(via Konrad and Richard Akerman) There was an interesting conference organized by Alen press - Emerging Trends in Scholarly Publishing. Both Konrad and Richard Akerman describe in their blogs what the conference was about and what they talked about.

in sillico network reconstruction (using expression data)

In my last post I commented on a paper that tried to find the best mathematical model for a cellular pathway. In that paper they used information on known and predicted protein interactions. This time I want to mention a paper, published in Nature Mol. Systems Biology, that attempts to reconstruct gene regulatory networks from gene expression data and Chip-chip data.

The authors were interested in determining how/when transcription factors regulate their target genes over time. One novelty introduced in this work was the focus on bifurcation events in gene expression. They tried to look for cases where a groups of genes clearly bifurcated into two groups at a particular time point. Combining these patterns of bifurcation with experimental binding data for transcription factors they tried to predict what transcription factors regulate these group of genes. There is a simple example shown in figure 1, reproduced below.


In this toy example there is a bifurcation event at 1 h and another at the 2h time point. All of the genes are assigned to a gene expression path. In this case, the red genes are those that are very likely to show a down regulation in between the 1st and 2nd hour and stay at the same level of expression from then on. Once the genes have been assigned it is possible to search for transcription factors that are significantly associate to each gene expression path. For example in this case, TF A is strongly associated to the pink trajectory. This means that many of the genes in the pink group have a known binding site for TF A in their promoter region.


To test their approach, the authors studied the amino-acid starvation in S. cerevisiae. In figure 2 they summarize the reconstructed dynamic map. The result is the association of TFs to groups of genes and the changes in expression of these genes over time during amino acid starvation.

One interesting finding from this map was that Ino4 activates a group of genes related to lipid metabolism starting at the 2h time point. Since Ino4 binding sites had only been profiled by Chip-chip in YPD media and not in a.a. starvation, this is a novel result obtained using their method.

To further test the significance of their observation they performed Chip-chip assays of Ino4 in amino acid starvation. They confirmed that Ino4 binds many more promoters during amino acid starvation as compared to synthetic complete glucose media. Out of 207 genes bound by Ino4 (specifically during AA starvation) 34 were also among the genes assigned to the Ino4 gene path obtained from their approach.

This results confirmed the usefulness of this computational approach to reconstruct gene regulatory networks from gene expression data and TF binding site information.
The authors then go on to study the regulation of other conditions.


For anyone curious enough about the method, this was done using Hidden Markov Models (see here for available primer on HMMs).

In silico network reconstruction

It is day one of Just Science week and I want to tell you about a recent paper that was published in BMC Systems Biology by Rui Alves and Albert Sorribas. It is about a general approach to integrate information to come up with models for cellular pathways. What does this mean and why is this important ?

Increasingly the scientific knowledge is being stored in databases (literature, protein structures, gene expression, protein-protein interactions, protein-DNA interactions, etc). The general idea behind the work described is that we should be able to use the accumulated information about cellular pathways to extract models of how the cell's components interact to preform their functions. By models I mean a formal representation that can tell us how the components' concentrations and activities change with time.

There are several works already dealing with this problem of trying to reconstruct cellular networks from large data sources but I found this article particularly interesting because it uses so many of these methods.

To give you an idea I reproduce below figure 4 of the paper with a diagram of the method (click to zoom in):




The authors have pulled in experimentally known interactions and combined them with putative interactions obtained from docking and phylogenetic based predictions. These predicted networks are then converted to several possible mathematical models that are examined under different parameter conditions and compared with known experimental values.

This method should be particularly suited for a case when some of the genes in the pathway are known and there are experimental measured outputs for the pathway that can be compared with the predictions from the putative pathway models.

Ideally this whole procedure would be fully converted into an automatic pipeline that could be used by people that are not so familiar with the tools.

I will try to stick with the same theme during the week, hopefully covering different methods to achieve the same thing.

Just Science

(Via RPM, Razib, Chris, Arunn) Next week is Just Science week. I will try to review recent papers on cellular networks, systems/synthetic biology and evolution that I found interesting.

Not so silent mutations


DNA mutations that do not change the coding amino-acid are many times referred to as "silent mutations", or synonymous mutations, because it is less likely that they will result in a change in function. Synonymous mutations are often considered to be evolutionary neutral and the ratio of non-synonymous substitutions (Ka) to synonymous substitutions (Ks) is used to study sequence evolution. It can be used for example to search for DNA regions targeted by selection (see review and a practical application).


In the last issue of Science Kimchi-Sarfaty and colleagues found a synonymous mutation in a transport protein that has an effect on the protein function. They have shown, at least in cell-lines, that the mutation does not affect mRNA levels nor the produced protein sequence. Finally the authors showed that the mutation might change the protein's conformation by comparing the sensibility of wild type and mutated sequence to trypsin digestion.

The authors speculate that the usage of that particular codon, even if not affecting the coding region, might change the translation rate and folding of the protein. It had already been shown in E. coli that synonymous mutations can affect the in vivo folding of a protein. Here the authors have shown a case where a silent mutation can change the substrate specificity of a transporter.

Because of these codon preferences it is important to adjust for codon selection pressures when studying synonymous substitutions. The codon preferences are usually considered to be due to differences in the pool of the cognate tRNA but other studies have shown that codon bias might arise also by codon context. In E. coli, codon pair preferences, were observed to affect their in vivo translation. Also, these codon pair preferences are species specific and are, at least in part, influenced by nucleotide positions within A-site tRNA sequences.

Hypothesis: If codon pairs can be selected due to tRNA structural constrains on the ribosome P and A sites then it might be necessary to correct for these codon preferences when studying synonymous mutations.

System Biology quick links

(via Pierre) BMC System Biology has published their first papers. More or less at the same time the new Systems and Synthetic Biology (published by Springer Netherlands) has started publishing papers. These two journals join IEE Systems Biology and Molecular Systems Biology (Nature/EMBO) as forums to publish works on Systems and Synthetic Biology. All journals (with the exception of IEE Systems Biology) publish in open access or at least (in the case of Systems and Synthetic Biology) offer an open access option.

Some of the talks from the BioSysBio conference are online in Goggle Video.

Here is a nice talk from Alfonso Valencia talking about species co-evolution and a very promising improvement to a sequence based method to predict protein-protein interactions:

Scientific Journals blog

Blogs have been around for some time. From the wikepedia:

The term "weblog" was coined by Jorn Barger on 17 December 1997. The short form, "blog," was coined by Peter Merholz, who jokingly broke the word weblog into the phrase we blog in the sidebar of his blog Peterme.com in April or May of 1999.

Blogs in science, on the other hand, have only recently become popular. The first two traditional science news journals to pick up the raising interest in scientific blogging were The-Scientist in August 2005, and then Nature in December 2005. Since then many more scientist have picked up blogging for a variety of purposes (see review by Coturnix). The science journals have been slowly reacting. Here is a current list of blogs from science journal blogs or publishing groups. If anyone knows more please leave a comment and I will add them to the list.

Journal	Blog
The Scientist	The Scientist Blog
Scientific American	SCIAM Observations
Nature publishing group
Nature Journals	List
Nature Genetics	Action Potential
Nature Neuroscience	Free Association
Nature Methods	Methagora
Nature Medicine	Spoonful of Medicine
Nature News	Nature Newsblog
Chemistry at Nature (portal not journal)	The Sceptical Chymist
Nature publishing group	Nascent
Nature publishing group	Nautilus
Nature publishing group	Peer-to-peer
Heredity	Inherently Responsive
Public Library of Science
PLoS Blogs	List
PLoS publishing	Publishing blog
PLoS Technology	Technology blog
PLoS Medicine	PLoS Medicine blog
The Lancet	The Lancet blog
Science	The Weblog of Science Magazine"s (stopped)

Science Blogging Anthology 2006

I mentioned before that Coturnix was getting ready a list of blog posts that would go into a science blogging anthology of 2006. Twelve judges have selected 50 blog posts that will be put together in a book. The book will then be published by lulu. The judges were nice enough to select one of my posts to go in the book :)

Opening up the scientific process

Science Blogging Anthology

Coturnix from a Blog Around the Clock is organizing a science blogging anthology. I missed it during the Christmas holidays but the results are due in a couple of days. Here is the list of posts that got nominated and are now being evaluated. One of my posts made the nomination list :) cool.

Last month Roland Krause said that this type of vanity posts (like blog carnivals) are similar to spam blogs. I actually think that there is value in carnivals and other equivalent content promotion activities. They create a cheap reward system that motivates people to produce more and better content. They also provide with a layer of quality rating even if, in the case of carnivals, the posts that are submitted are self contributed. Bloggers tend to submit their best content to the carnivals.

On a related note but with a very different opinion, here is a rant on Web 2.0 And Narcissism (via Rough Type):

"What he's getting at is that this whole Web 2.0, social networking, virtual community business is essentially a pornography of the self—a projected, fictionalized self that is then worshipped by the slightly less-perfect self."