Acrophile: an automated acronym extractor and server
DL '00 Proceedings of the fifth ACM conference on Digital libraries
Automatic Extraction of Biological Information from Scientific Text: Protein-Protein Interactions
Proceedings of the Seventh International Conference on Intelligent Systems for Molecular Biology
Using Compression to Identify Acronyms in Text
DCC '00 Proceedings of the Conference on Data Compression
A Probabilistic Model for Identifying Protein Names and their Name Boundaries
CSB '03 Proceedings of the IEEE Computer Society Conference on Bioinformatics
Text mining: generating hypotheses from MEDLINE
Journal of the American Society for Information Science and Technology
Enhancing performance of protein and gene name recognizers with filtering and integration strategies
Journal of Biomedical Informatics - Special issue: Named entity recognition in biomedicine
A hybrid approach to protein name identification in biomedical texts
Information Processing and Management: an International Journal
Artificial Intelligence in Medicine
A text-mining technique for extracting gene-disease associations from the biomedical literature
International Journal of Bioinformatics Research and Applications
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We present a statistical method that can swiftly identify, from the literature, sets of genes known to be associated with given diseases. It offers a comprehensive way to treat alias symbols, a statistical method for computing the relevance of the gene to the query, and a novel way to disambiguate gene symbols from other abbreviations. The method is illustrated by finding genes related to breast cancer.