Dr Casey Bergman

Publications

BioContext: an integrated text mining system for large-scale extraction and contextualization of biomolecular events
Martin Gerner, Farzaneh Sarafraz, Casey M Bergman, Goran Nenadic Bioinformatics. Oxford University Press; 2012
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pubmed2ensembl: A resource for mining the biological literature on genes
Baran, J., Gerner, M., Haeussler, M., Nenadic, G. and Bergman, C. M. PLoS One; 2011
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pubmed2ensembl: Linking Publications and Genes
Baran J, Gerner M, Haeussler M, Nenadic G, Bergman C. Genome Informatics (UK) 2010. Hinxton, UK; 2010
Gene mention normalization in full texts using GNAT and LINNAEUS
Illes Solt, Martin Gerner, Philippe Thomas, Goran Nenadic, Casey M. Bergman, Ulf Leser, Jorg Hakenberg Proceedings of the BioCreative III Workshop: BioCreative III Workshop. Bethesda, Maryland, USA; 2010
An Exploration of Mining Gene Expression Mentions and their Anatomical Locations from Biomedical Text
Gerner M., Nenadic, G., Bergman, C. M Proceedings of the BioNLP 2010 Workshop: BioNLP 2010 Workshop. Uppsala, Sweden; 2010
LINNAEUS: A species name identification system for biomedical literature
Gerner M., Nenadic, G., Bergman, C. M. BMC Bioinformatics. BioMed Central ; 2010
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Assigning Roles to Protein Mentions: the Case of Transcription Factors
Yang, H., Keane, J., Bergman, C., Nenadic, G. Journal of Biomedical Informatics; 2009
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Named-entity recognition and term mining

Recognizing terms and named entities in research articles and mapping them to unique identifiers is an important first step in most text mining software. This is a challenging task because of ambiguity and variation in how entities and concepts are named and used in particular in the biological literature. Our…
Mining term associations and events from bio-literature

This is a long-term project that aims at developing text mining methods that can provide efficient and sophisticated knowledge acquisition, offer plausible hypotheses for testing, prevent unnecessary repetition of previous work, and help in experimental design for specific research scenarios. We investigate various text mining approaches to establishing literature-based associations…
Integration of text and data mining in life sciences

There have been numerous efforts to provide tools for storing, extracting and analysing data in life sciences. Interoperability and integration of such efforts is a challenging issue, not only technically (e.g. different formats, protocols, encodings) but also more importantly semantically. We are involved in a number of community-driven initiatives to…