An overview of BioCreative II.5

Florian Leitner, Scott A. Mardis, Martin Krallinger, Gianni Cesareni, Lynette A. Hirschman, Alfonso Valencia

Research output: Contribution to journalArticlepeer-review

Abstract

We present the results of the BioCreative II.5 evaluation in association with the FEBS Letters experiment, where authors created Structured Digital Abstracts to capture information about protein-protein interactions. The BioCreative II.5 challenge evaluated automatic annotations from 15 text mining teams based on a gold standard created by reconciling annotations from curators, authors, and automated systems. The tasks were to rank articles for curation based on curatable protein-protein interactions; to identify the interacting proteins (using UniProt identifiers) in the positive articles (61); and to identify interacting protein pairs. There were 595 full-text articles in the evaluation test set, including those both with and without curatable protein interactions. The principal evaluation metrics were the interpolated area under the precision/recall curve (AUC iP/R), and (balanced) F-measure. For article classification, the best AUC iP/R was 0.70; for interacting proteins, the best system achieved good macroaveraged recall (0.73) and interpolated area under the precision/recall curve (0.58), after filtering incorrect species and mapping homonymous orthologs; for interacting protein pairs, the top (filtered, mapped) recall was 0.42 and AUC iP/R was 0.29. Ensemble systems improved performance for the interacting protein task.

Original languageEnglish
Article number5535012
Pages (from-to)385-399
Number of pages15
JournalIEEE/ACM Transactions on Computational Biology and Bioinformatics
Volume7
Issue number3
DOIs
Publication statusPublished - 2010

Keywords

  • biological curation.
  • molecular biology
  • natural language processing
  • text analysis
  • Text mining

ASJC Scopus subject areas

  • Biotechnology
  • Genetics
  • Applied Mathematics
  • Medicine(all)

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