e-LiSe (e-Literature Searcher) is an easy-to-use web-based application which finds biomedical information truly related to English words provided by the user. The program uses PubMed database of scientific abstracts as the source of data and a novel bio-linguistic statistical method (based on Z-score), to discover true correlations, even when they are low-frequency associations.

e-LiSe is also capable of finding names of researchers correlated to the information searched by the user. It can function as a name reference engine, answering questions like “who is working on specified subject?” or “what are the coworkers/collaborators of a certain person?”. For the latter the software uses the list of co-authors of each publication a researcher has written to display connections between scientists.

Data analysed by e-LiSe comprises of about 17 millions abstracts. To improve the programs' performance a threshold has been set for the number of abstracts that can be processed for a single query (50 thousand abstracts). When the user submits a query with demands a larger abstracts set, e-LiSe will ask to refine the query.

(new) More sophisticated ways of searching with e-LiSe are now possible.Full support for queries with logical operators (AND, OR and NOT), prioritized by the means of brackets, has just been introduced read more

(new) e-LiSe usability was thoroughly tested. We created automated test to check the value of e-LiSe-generated information about hereditary diseases.read more

(new) Application note about e-LiSe has just been published in Bioinformatics. You can find it here