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Last week, I attended the Midwest Consortium’s annual conference.  The goal was to network with other scholars in the region to facilitate collaboration and development of potential grant proposals.  I got to meet Dr. Joyce Hunter, Deputy Director of the NIH National Center (soon to be Institute) on Minority Health and Health Disparities.  She gave a presentation on different funding mechanisms available at NIH, and described a timeline for applying for those mechanisms depending on where you are in your career.  Dr. Hunter emphasized that NIH is moving away from the path of R03 > R15/R21 > R01, and more toward career development awards (F32, K30, K99/R00) as a means of becoming an independent researcher.  She noted that her center now has a few R01 funding opportunities available, and that NIH has adopted a streamlining process for new investigators, so that they form a separate pool of applications.  Of the 20 R01 grants funded by NCMHD last cycle, 10 were from new investigators. Of those, 8 had had previous NIH funding (many through the Loan Repayment Program).

For those still trying to familiarize themselves with the seemingly Byzantine workings of the nation’s top funding agency, here are two videos from the NIH Center for Scientific Review on what happens at a review panel and advice for new applicants.

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Also, check the NIH Office of Extramural Research for current funding opportunities, grant application basics, and information on forms and deadlines.

ResearchBlogging.orgThere’s an interesting piece in the most recent issue of Nature.  Corie Lok discusses how researchers are dealing with the information firehose that is scientific literature.  How big is that firehose?

The 19 million citations and abstracts covered by the US National Library of Medicine’s PubMed search engine include nearly 830,000 articles published in 2009, up from some 814,000 in 2008 and around 772,000 in 2007. That growth rate shows no signs of abating, especially as emerging countries such as China and Brazil continue to ratchet up their research.

With that amount of data overload, how is an established researcher going to keep up with relevant work in their field? Nevermind how a new investigator can get a handle on establishing a research focus, or a midcareer scientist switch tracks.  That’s where literature mining comes in.  There are several start-up services on the web to help scientists find relevant research, make connections, and generate hypotheses. A few of these are discussed in Lok’s article, but there are many others.

PubMed – My default search engine for research papers, this is the first stop for many scientists.  So let’s try a little experiment.  Searching “alcoholism” generates the following – Results: 1 to 20 of 66827. PubMed does have tools to help you narrow your search.  Say I’m interested in the genetics of alcoholism. Searching “alcoholism genetics” returns – Results: 1 to 20 of 5940. A lot of research to go through. Restricting that search to only publications in the last 5 years, in English, and about humans gives Results: 1 to 20 of 1283. Still a lot of literature, even if you’re only reading the abstracts.

That’s where literature mining can really make a difference.

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