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EVEX: a PubMed-scale resource for homology-based generalization of text mining predictions

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Bioinformatics: from nucleotids to networks (N2N)
Abstract
In comparative genomics, functional annotations are transferred from one organism to another relying on sequence similarity. With more than 20 million citations in PubMed, text mining provides the ideal tool for generating additional large-scale homology-based predictions. To this end, we have refined a recent dataset of biomolecular events extracted from text, and integrated these predictions with records from public gene databases. Accounting for lexical variation of gene symbols, we have implemented a disambiguation algorithm that uniquely links the arguments of 11.2 million biomolecular events to well-defined gene families, providing interesting opportunities for query expansion and hypothesis generation. The resulting MySQL database, including all 19.2 million original events as well as their homology-based variants, is publicly available at http://bionlp.utu.fi/.

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Citation

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Chicago
Van Landeghem, Sofie, Filip Ginter, Yves Van de Peer, and Tapio Salakoski. 2011. “EVEX: a PubMed-scale Resource for Homology-based Generalization of Text Mining Predictions.” In Proceedings of the 2011 Workshop on Biomedical Natural Language Processing, 28–37. Association for Computational Linguistics (ACL).
APA
Van Landeghem, S., Ginter, F., Van de Peer, Y., & Salakoski, T. (2011). EVEX: a PubMed-scale resource for homology-based generalization of text mining predictions. Proceedings of the 2011 workshop on biomedical natural language processing (pp. 28–37). Presented at the Workshop on Biomedical Natural Language Processing (ACL-HLT 2011), Association for Computational Linguistics (ACL).
Vancouver
1.
Van Landeghem S, Ginter F, Van de Peer Y, Salakoski T. EVEX: a PubMed-scale resource for homology-based generalization of text mining predictions. Proceedings of the 2011 workshop on biomedical natural language processing. Association for Computational Linguistics (ACL); 2011. p. 28–37.
MLA
Van Landeghem, Sofie, Filip Ginter, Yves Van de Peer, et al. “EVEX: a PubMed-scale Resource for Homology-based Generalization of Text Mining Predictions.” Proceedings of the 2011 Workshop on Biomedical Natural Language Processing. Association for Computational Linguistics (ACL), 2011. 28–37. Print.
@inproceedings{2010416,
  abstract     = {In comparative genomics, functional annotations are transferred from one organism to another relying on sequence similarity. With more than 20 million citations in PubMed, text mining provides the ideal tool for generating additional large-scale homology-based predictions. To this end, we have refined a recent dataset of biomolecular events extracted from text, and integrated these predictions with records from public gene databases. Accounting for lexical variation of gene symbols, we have implemented a disambiguation algorithm that uniquely links the arguments of 11.2 million biomolecular events to well-defined gene families, providing interesting opportunities for query expansion and hypothesis generation. The resulting MySQL database, including all 19.2 million original events as well as their homology-based variants, is publicly available at http://bionlp.utu.fi/.},
  author       = {Van Landeghem, Sofie and Ginter, Filip and Van de Peer, Yves and Salakoski, Tapio},
  booktitle    = {Proceedings of the 2011 workshop on biomedical natural language processing},
  language     = {eng},
  location     = {Portland, OR, USA},
  pages        = {28--37},
  publisher    = {Association for Computational Linguistics (ACL)},
  title        = {EVEX: a PubMed-scale resource for homology-based generalization of text mining predictions},
  year         = {2011},
}