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EVEX: A PubMed-Scale Resource for Homology-Based Generalization of Text Mining Predictions

Sofie Van Landeghem, Filip Ginter, Yves Van de Peer, Tapio Salakoski, EVEX: A PubMed-Scale Resource for Homology-Based Generalization of Text Mining Predictions. In: Proceedings of BioNLP'11 Workshop, 28-37, ACL, 2011.

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/.

BibTeX entry:

@INPROCEEDINGS{inpVaGiVaSa11a,
  title = {EVEX: A PubMed-Scale Resource for Homology-Based Generalization of Text Mining Predictions},
  booktitle = {Proceedings of BioNLP'11 Workshop},
  author = {Van Landeghem, Sofie and Ginter, Filip and Van de Peer, Yves and Salakoski, Tapio},
  publisher = {ACL},
  pages = {28-37},
  year = {2011},
  keywords = {evex event extraction},
}

Belongs to TUCS Research Unit(s): Turku BioNLP Group

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