Overview of the BioCreative VI text-mining services for Kinome Curation Track.

ABSTRACT: The text-mining services for kinome curation track, part of BioCreative VI, proposed a competition to assess the effectiveness of text mining to perform literature triage. The track has exploited an unpublished curated data set from the neXtProt database. This data set contained comprehensive annotations for 300 human protein kinases. For a given protein and a given curation axis [diseases or gene ontology (GO) biological processes], participants' systems had to identify and rank relevant articles in a collection of 5.2 M MEDLINE citations (task 1) or 530 000 full-text articles (task 2). Explored strategies comprised named-entity recognition and machine-learning frameworks. For that latter approach, participants developed methods to derive a set of negative instances, as the databases typi

SUBMITTER: Gobeill J 

PROVIDER: S-EPMC6191643 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature