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Exploring biomolecular literature with EVEX : connecting genes through events, homology, and indirect associations

Sofie Van Landeghem (UGent) , Kai Hakala, Samuel Rönnqvist, Tapio Salakoski, Yves Van de Peer (UGent) and Filip Ginter
(2012) ADVANCES IN BIOINFORMATICS. 2012.
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Abstract
Technological advancements in the field of genetics have led not only to an abundance of experimental data, but also caused an exponential increase of the number of published biomolecular studies. Text mining is widely accepted as a promising technique to help researchers in the life sciences deal with the amount of available literature. This paper presents a freely available web application built on top of 21.3 million detailed biomolecular events extracted from all PubMed abstracts. These text mining results were generated by a state-of-the-art event extraction system and enriched with gene family associations and abstract generalizations, accounting for lexical variants and synonymy. The EVEX resource locates relevant literature on phosphorylation, regulation targets, binding partners, and several other biomolecular events and assigns confidence values to these events. The search function accepts official gene/protein symbols as well as common names from all species. Finally, the web application is a powerful tool for generating homology-based hypotheses as well as novel, indirect associations between genes and proteins such as coregulators.
Keywords
biology computing, proteins, text analysis, molecular biophysics, data mining, genetics, Internet

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MLA
Van Landeghem, Sofie, et al. “Exploring Biomolecular Literature with EVEX : Connecting Genes through Events, Homology, and Indirect Associations.” ADVANCES IN BIOINFORMATICS, vol. 2012, 2012, doi:10.1155/2012/582765.
APA
Van Landeghem, S., Hakala, K., Rönnqvist, S., Salakoski, T., Van de Peer, Y., & Ginter, F. (2012). Exploring biomolecular literature with EVEX : connecting genes through events, homology, and indirect associations. ADVANCES IN BIOINFORMATICS, 2012. https://doi.org/10.1155/2012/582765
Chicago author-date
Van Landeghem, Sofie, Kai Hakala, Samuel Rönnqvist, Tapio Salakoski, Yves Van de Peer, and Filip Ginter. 2012. “Exploring Biomolecular Literature with EVEX : Connecting Genes through Events, Homology, and Indirect Associations.” ADVANCES IN BIOINFORMATICS 2012. https://doi.org/10.1155/2012/582765.
Chicago author-date (all authors)
Van Landeghem, Sofie, Kai Hakala, Samuel Rönnqvist, Tapio Salakoski, Yves Van de Peer, and Filip Ginter. 2012. “Exploring Biomolecular Literature with EVEX : Connecting Genes through Events, Homology, and Indirect Associations.” ADVANCES IN BIOINFORMATICS 2012. doi:10.1155/2012/582765.
Vancouver
1.
Van Landeghem S, Hakala K, Rönnqvist S, Salakoski T, Van de Peer Y, Ginter F. Exploring biomolecular literature with EVEX : connecting genes through events, homology, and indirect associations. ADVANCES IN BIOINFORMATICS. 2012;2012.
IEEE
[1]
S. Van Landeghem, K. Hakala, S. Rönnqvist, T. Salakoski, Y. Van de Peer, and F. Ginter, “Exploring biomolecular literature with EVEX : connecting genes through events, homology, and indirect associations,” ADVANCES IN BIOINFORMATICS, vol. 2012, 2012.
@article{2974155,
  abstract     = {{Technological advancements in the field of genetics have led not only to an abundance of experimental data, but also caused an exponential increase of the number of published biomolecular studies. Text mining is widely accepted as a promising technique to help researchers in the life sciences deal with the amount of available literature. This paper presents a freely available web application built on top of 21.3 million detailed biomolecular events extracted from all PubMed abstracts. These text mining results were generated by a state-of-the-art event extraction system and enriched with gene family associations and abstract generalizations, accounting for lexical variants and synonymy. The EVEX resource locates relevant literature on phosphorylation, regulation targets, binding partners, and several other biomolecular events and assigns confidence values to these events. The search function accepts official gene/protein symbols as well as common names from all species. Finally, the web application is a powerful tool for generating homology-based hypotheses as well as novel, indirect associations between genes and proteins such as coregulators.}},
  articleno    = {{582765}},
  author       = {{Van Landeghem, Sofie and Hakala, Kai and Rönnqvist, Samuel and Salakoski, Tapio and Van de Peer, Yves and Ginter, Filip}},
  issn         = {{1687-8027}},
  journal      = {{ADVANCES IN BIOINFORMATICS}},
  keywords     = {{biology computing,proteins,text analysis,molecular biophysics,data mining,genetics,Internet}},
  language     = {{eng}},
  pages        = {{12}},
  title        = {{Exploring biomolecular literature with EVEX : connecting genes through events, homology, and indirect associations}},
  url          = {{http://doi.org/10.1155/2012/582765}},
  volume       = {{2012}},
  year         = {{2012}},
}
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