Social networking sites reviewed...

Here is a link to a blog item from Comprendia, the Biosciences Consulting Group. It is a good review of the some of the current social networking sites available to life scientists and the usage they get. As the authors says, these figures may not be totally accurate, but they do give an indication that some of these sites at least are gaining traction in the community.

Click here is see an earlier list of sites posted here last year.

On the reading habits of the digital generation...

Read a nice summary by Martin Fenner on digital reading habits across formats. It will kindle your imagination...

Welcome to Jane...

Jane stands for Journal/Author Name Estimator. None the wiser...?!

Have you recently written a paper, but you are not sure which journal to submit it to? Or maybe you want to find related articles so that you can identify a suitable referee.

Then just cut and paste the abstract of the paper into Jane and it (she?) will search Medline to find matching articles, journals and authors. It's like eTBlast - see earlier post.

Nice tools, but you should be able to do this with PubMed or Scopus.

Text mining with GeneIndexer

GeneIndexer has been around now for a couple of years but seems too be getting some marketing dollars spent on it with a full page advertisement in the latest issue of Nature and a sale to the NIH Library. The tool enables researchers to reveal biological significance in a set of co-regulated or associated genes. Applications include:

• Using keywords to identify and prioritize genes most relevant to any given research question. Keywords can be any string of words, e.g. disease names, molecular pathways, or Gene Ontology classifications.
• Uncovering implicit, as well as explicit, functional relationships among genes--discover new genes and propose hypotheses above and beyond what is explicitly described in the literature.
• Building hierarchical trees of genes in which gene subsets are clustered into functionally related groups. This allows researchers to navigate large gene collections easily and adds a new dimension to the analysis and discovery process.

Because GeneIndexer includes all of the genes contained in Entrez Gene and OMIM databases, and uses artificial intelligence and computational linguistic techniques, rather than human curators to identify conceptual gene relationships it is possibly the most up-to-date and accurate system of its kind.

eTBLAST 3.0: a similarity-based search engine

I have only just come across eTBlast. Conceptually, it is a bit like NCBI's Blast utility wich assesses sequence similarites between geens or proteins. Here, you simply in put a paragraph of text and eTBLAST will return the abstracts of articles which use the same spectrum of terms. It works a little like PubMed's Related Article feature, except here you can supply your own text, which could be from an unpublished article or a research proposal. New features in version 3.0 include "Find an Expert" - identifies authors that are the most published in the topic of your query - and "Find a Journal" - identifies journals that published on your topic the most.

In this day and age of increasingly specialized science, it can often be a non-trivial task to identify an appropriate journal to submit to. And editors are forever trying to identify appropriate referees - so eTBLAST seems to fill a worthwhile niche.

Open access to federally funded research - a public debate

Currently, the National Institutes of Health is the only federal body that requires that research funded by its grants be made available to the public online at no charge within 12 months of publication. The US Administration is seeking views as to whether this policy should be extended to other science agencies and, if so, how it should be implemented. You can follow the discussion at the OSTC Blog.

The discussion will occur in three major phases:

• Implementation: Which Federal agencies are good candidates to adopt Public Access policies? What variables (field of science, proportion of research funded by public or private entities, etc.) should affect how public access is implemented at various agencies, including the maximum length of time between publication and public release?
• Features and Technology: In what format should the data be submitted in order to make it easy to search and retrieve information, and to make it easy for others to link to it? Are there existing digital standards for archiving and interoperability to maximize public benefit? How are these anticipated to change.
• Management: What are the best mechanisms to ensure compliance? What would be the best metrics of success? What are the best examples of usability in the private sector (both domestic and international)? Should those who access papers be given the opportunity to comment or provide feedback?

A wrap up of phase one is posted here. It provides an interesting overview of how the opportunities presented by Open Access are seen by different research communities.

Google Wave hits biology beach...

If you want to see some interesting Google Wave applications being developed for the life sciences, visit this link! If you have time, take a look around, it is an interesting blog.