LAITOR - Literature Assistant for Identification of Terms co-Occurrences and Relationships

<p>Abstract</p> <p>Background</p> <p>Biological knowledge is represented in scientific literature that often describes the function of genes/proteins (bioentities) in terms of their interactions (biointeractions). Such bioentities are often related to biological concepts of interest that are specific of a determined research field. Therefore, the study of the current literature about a selected topic deposited in public databases, facilitates the generation of novel hypotheses associating a set of bioentities to a common context.</p> <p>Results</p> <p>We created a text mining system (LAITOR: <it><b>L</b>iterature <b>A</b>ssistant for <b>I</b>dentification of <b>T</b>erms co-<b>O</b>ccurrences and <b>R</b>elationships</it>) that analyses co-occurrences of bioentities, biointeractions, and other biological terms in MEDLINE abstracts. The method accounts for the position of the co-occurring terms within sentences or abstracts. The system detected abstracts mentioning protein-protein interactions in a standard test (BioCreative II IAS test data) with a precision of 0.82-0.89 and a recall of 0.48-0.70. We illustrate the application of LAITOR to the detection of plant response genes in a dataset of 1000 abstracts relevant to the topic.</p> <p>Conclusions</p> <p>Text mining tools combining the extraction of interacting bioentities and biological concepts with network displays can be helpful in developing reasonable hypotheses in different scientific backgrounds.</p