AZuRE, a Scalable System for Automated Term Disambiguation of Gene and Protein Names
CSB '04 Proceedings of the 2004 IEEE Computational Systems Bioinformatics Conference
HLT '91 Proceedings of the workshop on Speech and Natural Language
Gene name ambiguity of eukaryotic nomenclatures
Bioinformatics
Gene symbol disambiguation using knowledge-based profiles
Bioinformatics
Selecting an ontology for biomedical text mining
BioNLP '09 Proceedings of the Workshop on Current Trends in Biomedical Natural Language Processing
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Since there is no standard naming convention for genes and gene products, gene symbol disambiguation (GSD) has become a big challenge when mining biomedical literature. Several GSD methods have been proposed based on MEDLINE references to genes. However, nowadays gene databases, e.g. Entrez Gene, provide plenty of information about genes, and many biomedical ontologies, e.g. UMLS Metathesaurus and Semantic Network, have been developed. These knowledge sources could be used for disambiguation, in this paper we propose a method which relies on information about gene candidates from gene databases, contexts of gene symbols and biomedical ontologies. We implement our method, and evaluate the performance of the implementation using BioCreAtIvE II data sets.