Wen-Juan Hou (email@example.com)
Kevin Hsin-Yih Lin (firstname.lastname@example.org)
Hsin-Hsi Chen (email@example.com)
Department of Computer Science and Information Engineering, National Taiwan University, No.1, Sec.4, Roosevelt Road, Taipei, Taiwan 106
Gene Ontology (GO) is developed to provide standard vocabularies of gene products in different databases. The process of annotating GO terms to genes requires curators to read through lengthy articles. Methods for speeding up or automating the annotation process are thus of great importance. We propose a GO annotation approach using full-text biomedical documents for directing more relevant papers to curators. This system explores word density and gravitation relationships between genes and GO terms. Different density and gravitation models are built and several evaluation criteria are employed to assess the effects of the proposed methods.