nodalpoint.org - Literature - Comments

More like these to come

badboyz — Fri, 11 May 2007 04:40:11 -0400

I think more and more people will be getting into this strategy at the beginning because 454's method much to be desired. On the other hand I think we should look carefully at how ABI is going to handle this new and emerging market. Their new high-throughput sequencer, SOLID, is based on the Agencourt sytem.

What would be really cool is if we could get a machine that could interchange modes. Quite an instrumentation challenge because one technology is bead-based (454) - not sure about SOLID - and the other is clone based (Sanger).

How to Link/Deduplicate Citation Records

Bob Carpenter — Mon, 13 Nov 2006 12:25:55 -0500

To answer the how question, check out William Cohen et al.'s excellent 2003 overview paper, A Comparison of String Metrics for Matching Names and Records. I chose this paper of the dozens out there because it has good references and William also works in bio-informatics, so you may see him around.

There was a recent spate of papers on the topic, because academic citation linkage was the topic of the 2003 KDD Cup Competition which is part of ACM's SIGKDD (the Association for Computing Machinery's special interest group in knowledge discovery and data mining).

Bob Carpenter

Alias-i, Inc.

Thanks for all the useful

FiReaNG3L — Fri, 10 Nov 2006 22:03:49 -0500

Thanks for all the useful answers everyone! I really really really hope that OTMI takes off big time (like, every publisher/journal) - it would help tremendously. Right now, only Nature is behind this, right?

Too bad Scopus chose to go the proprietary route - with their reference database and their new author disambiguation, it would beat pubmed hands down. I just became aware of it a week ago; no researchers that I know of had even heard of it, and our university have a subscription! Go figure...

blow for freedom

Neil — Fri, 10 Nov 2006 09:21:41 -0500

Elsevier probably wouldn't be very happy...

No, but Elsevier is the antichrist. So ultimately, it's justified.

Elsevier probably wouldn't be very happy...

stewc — Fri, 10 Nov 2006 06:48:14 -0500

... if you scraped references from their non-OA journals to create a competitor to SCOPUS. :)

You could work with the subset of journals in PubMedCentral & BMC - that way you get a lot of data but only need to work out how to scrape (or parse the embedded RDF in) two different manuscript templates. Maybe the data wouldn't be representative enough of the literature as a whole, though, I don't know.

Ideally there'd be reference metadata linked to in the header of every paper and you could do everything dynamically - type in an URL and it retrieves the reference list from that paper, then use the URLs of those papers, etc.

(plug:) OTMI might eventually enable that.

Google Scholar basically

alf — Fri, 10 Nov 2006 06:39:57 -0500

Google Scholar basically supercedes CiteSeer, and HubMed only has citation data from PubMed Central. The OpCit project attempted to make an open citation database from OAI archives and produced CiteBase, for searching citations.

Citeseer

dalloliogm — Fri, 10 Nov 2006 04:58:44 -0500

Hi,
do you know of Citeseer (http://citeseer.ist.psu.edu/)?
It's supposed to be a tool to browse in scientific citations.
Actually their search engine is not very funcional: you should use the google tag 'site:http://citeseer.ist.psu.edu/' to find an article correctly.
here is an example: http://citeseer.ist.psu.edu/6394.html (it gives you citations, graphs, etc..)

Or maybe you could use hubmed, it has some option to search citations.

citeXtract

ejain — Thu, 09 Nov 2006 19:50:12 -0500

This guy is working on a project called citeXtract, which might be pretty much what you are looking for (though I don't know what the current status of the project is).

Is bioinformatics a field?

Neil — Mon, 05 Jun 2006 02:09:19 -0400

I think it's difficult to rank researchers in "bioinformatics", because it's not really a research field. This is one of the major problems that we have in bridging the divide between computational and wet-lab biologists - the latter group see bioinformatics as a field, when in fact it's really a collection of mathematical, statistical and computational methods.

Your study is useful in that it highlights current inadequacies in ranking. How do we classify a bioinformatics researcher? If I include "bioinformatics" as a keyword in my paper, does that make it a bioinformatics paper? Just because I used BLAST or Clustal in there somewhere? How about people who work with genomes? They'll use a variety of computational methods, but is their main focus the methods or the biology of the genome under study? I'd argue the latter.

It helps to distinguish "bioinformatics" from "computational biology". There are a lot of people using the former and a very few people making advances with the latter. The names that you mentioned are certainly people who have applied novel algorithms to aid the classification and analysis of biological data (mostly structural data in those cases).

What of the many people who have input into tool development - things like the Bio* projects, or Gbrowse, or HMMER, or the many useful databases such as Pfam, InterPro, SuperFamily? Does it really make sense to rank those people based on who the first and last authors were? I would argue that it doesn't.

This is why many of us feel that the bioinformatics era, with its ethos of open source, global collaboration, public data and true cross-disciplinary approaches is rather at odds with the old-school way of doing science (become head of lab, choose niche, make name, cultivate ego). In other words, I'm not sure that ranking individuals really means a lot in this brave new world.

Having said that there certainly are influential individuals - let me nominate Lincoln Stein, Sean Eddy and Ewan Birney as examples. Contributions by these people and many others are measured by far more than citations.

M Katoh has certainly gamed

ionchannels — Mon, 05 Jun 2006 00:41:04 -0400

M Katoh has certainly gamed my ranking algorithm. As mentioned by others, the journals are highly suspect and he even publishes many of these "articles" using a second M Katoh (his wife??) in the author list to get double credit for each publication. Sander, Thornton, and Bork should be considered the true top 3 in bioinformatics research. What do others think are the most influential scientists in this field?

Greg, I was referring to the

ionchannels — Sun, 04 Jun 2006 15:54:52 -0400

Greg, I was referring to the scientist ranking system http://www.biolicious.com/rankings.php. Those are good suggestions for the literature browser, thanks...

Bioinformatics top researcher

chris — Sun, 04 Jun 2006 14:48:15 -0400

I notice that our old friend M Katoh tops the PI list for bioinformatics...

I notice that the site

Greg — Sun, 04 Jun 2006 13:40:15 -0400

I notice that the site navigation is a little different, but other than that how has the site changed since you last posted it ? I recall that the previous version also had a citation ranking system. How do you do the ranking ? is there a way to combine tags ? e.g. bioinformatics+transcription+factors ? in the same way that delicious does ? what about relevance ?

Also some of the tags on the stem cells tag cloud page seem to be messing the last letter e.g. angiogenesi, centrosom, cultur, imag...

Don't forget that if you want to announce updates to your site/software please do that in the appropriate forum. Forum posts don't go via the submission queue.

A Hirsch-type index for journals

PedroBeltrao — Tue, 22 Nov 2005 06:47:26 -0500

The last issue of The Scientist has a letter by Tibor Braun, Wolfgang Glänzel and András Schubert on extending the H-index to journals. They compared the top 10 journals ranked by H-index with the ranking by impact factor to highlight some of the differences between the two ratings. Down go the review only journals and up come some higher volume journals line PNAS and JBC.

Thanks

chris — Sat, 17 Sep 2005 23:40:24 -0400

Thanks for that, Pedro. I'm familiar with the people you mention (although I didn't know Barabasi was moving to DFCI). You are, as usual, right - combining ppi and expression data is *probably* a sane idea. But how stable are expression results, and can you predict phenotypes based on these changes in the transcriptome? That's where I'm going with this...