There are two new tools available that mine semantically PubMed abstracts, e-LiSe and Anne O’Tate. First one was made by my colleagues from Institute of Biochemistry and Biophysics in Warsaw, while the second is from University of Illinois, Chicago. Female-sounding names is not the only thing that makes them look similar, they both provide analogous functionality, like keywords or author names associated with user query.
There’s quite a lot of third party interfaces to PubMed (see David Rothman’s excellent list), so I couldn’t resist to run few queries on both servers and compare them to GoPubmed, which currently wins hands down in terms of features and interface. I wasn’t surprised to see that results overlap significantly, although not completely. Each of servers found valuable keywords other two did not have – that’s understandable, they use different algorithms. I wonder if we will see a meta-server of PubMed data-miners, like there are for protein structure prediction (for example meta.bioinfo.pl). In theory, exhaustive search for meaningful keywords by different methods and then their classification and analysis should work better than any single method, but this is just a guess.