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

ADRIANO BARBOSA-SILVA; THEODOROS G SOLDATOS; IVAN LUIZ FIORINI DE MAGALHÃES; GEORGIOS A PAVLOPOULOS; JEAN-FRED FONTAINE; MIGUEL A ANDRADE-NAVARRO; REINHARD SCHNEIDER; JOSÉ MIGUEL ORTEGA

BMC BIOINFORMATICS

BIOMED CENTRAL LTD

Lugar: Londres; Año: 2010 vol. 11 p. 1 - 15

1471-2105

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.We created a text mining system (LAITOR: Literature Assistant for Identification of Terms co-Occurrences and Relationships) 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. 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.