swMATH ID: 35376
Software Authors: Katrin Fundel, Robert Küffner, Ralf Zimmer
Description: RelEx - Relation extraction using dependency parse trees. Motivation: The discovery of regulatory pathways, signal cascades, metabolic processes or disease models requires knowledge on individual relations like e.g. physical or regulatory interactions between genes and proteins. Most interactions mentioned in the free text of biomedical publications are not yet contained in structured databases. Results: We developed RelEx, an approach for relation extraction from free text. It is based on natural language preprocessing producing dependency parse trees and applying a small number of simple rules to these trees. We applied RelEx on a comprehensive set of one million MEDLINE abstracts dealing with gene and protein relations and extracted  150 000 relations with an estimated perfomance of both 80
Homepage: https://academic.oup.com/bioinformatics/article/23/3/365/236564
Related Software: LIBSVM; OpenDMAP; ABNER; GENIA corpus; UniProt
Cited in: 0 Documents