UNIGE document Scientific Article
previous document  unige:1065  next document
add to browser collection

Gene Ontology density estimation and discourse analysis for automatic GeneRiF extraction

Tbahriti, Imad
Published in BMC bioinformatics. 2008, vol. 9 Suppl 3, S9
Abstract BACKGROUND: This paper describes and evaluates a sentence selection engine that extracts a GeneRiF (Gene Reference into Functions) as defined in ENTREZ-Gene based on a MEDLINE record. Inputs for this task include both a gene and a pointer to a MEDLINE reference. In the suggested approach we merge two independent sentence extraction strategies. The first proposed strategy (LASt) uses argumentative features, inspired by discourse-analysis models. The second extraction scheme (GOEx) uses an automatic text categorizer to estimate the density of Gene Ontology categories in every sentence; thus providing a full ranking of all possible candidate GeneRiFs. A combination of the two approaches is proposed, which also aims at reducing the size of the selected segment by filtering out non-content bearing rhetorical phrases. RESULTS: Based on the TREC-2003 Genomics collection for GeneRiF identification, the LASt extraction strategy is already competitive (52.78%). When used in a combined approach, the extraction task clearly shows improvement, achieving a Dice score of over 57% (+10%). CONCLUSIONS: Argumentative representation levels and conceptual density estimation using Gene Ontology contents appear complementary for functional annotation in proteomics.
Keywords AlgorithmsArtificial IntelligenceGenes/geneticsMEDLINENatural Language ProcessingPattern Recognition, Automated/methodsProteins/classification/geneticsSensitivity and SpecificityTerminology as TopicVocabulary, Controlled
PMID: 18426554
Full text
Research group Swiss-Prot Research Group
(ISO format)
GOBEILL, Julien et al. Gene Ontology density estimation and discourse analysis for automatic GeneRiF extraction. In: BMC bioinformatics, 2008, vol. 9 Suppl 3, p. S9. doi: 10.1186/1471-2105-9-S3-S9 https://archive-ouverte.unige.ch/unige:1065

496 hits



Deposited on : 2009-03-04

Export document
Format :
Citation style :