e-LiSe--an online tool for finding needles in the '(Medline) haystack'

Summary: Using literature databases one can find not only knownand true relations between processes but also less studied,non-obvious associations. The main problem with discoveringsuch type of relevant biological information is ‘selection’.The ability to distinguish between a true correlation (e.g.between different types of biological processes) and randomchance that this correlation is statistically significant iscrucial for any bio-medical research, literature mining beingno exception. This problem is especially visible when searchingfor information which has not been studied and described inmany publications. Therefore, a novel bio-linguistic statisticalmethod is required, capable of ‘selecting’ truecorrelations, even when they are low-frequency associations.In this article, we present such statistical approach basedon Z-score and implemented in a web-based application ‘e-LiSe’. Availability: The software is available at http://miron.ibb.waw.pl/elise/ Contact: piotr{at}ibb.waw.pl Supplementary information: Supplementary materials are availableat http://miron.ibb.waw.pl/elise/supplementary/ Associate Editor: Alfonso Valencia