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Table 1 Members of the UAG represent a diverse sample of end users with multiple text mining needs

From: BioCreative III interactive task: an overview

Domains represented by UAG members and Chair*
Model Organism Databases dictyBase, MGI, TAIR, Gramene, Wormbase
Protein Sequence Databases UniProtKB
Protein-Protein Interaction Databases BioGrid, MINT
Ontologies Gene Ontology, Protein Ontology, Plant Ontology, Microbial Phenotype Ontology
Pharmaceutical Companies Dupont, Merck KGaA, Pfizer
Examples of text mining needs among UAG members
□ gene normalization
□ mapping to ontologies (e.g., GO, PO, PRO) either for annotation or semantic integration
□ entity normalization and relevance scoring to help automate relationship extraction and data integration of text mined facts with external and internal sources
Identification of articles:
□ related to a specific topic (PPI, biomarkers)
□ reporting experimental information for gene/proteins in a given organism
□ with experimental characterization of gene/protein with associated reporting of organism and gene normalization when available
□ new articles not yet in the database
  1. *Note that some members represent more than one resource