An Overview of BioCreative II.5

Authors:
Florian Leitner;Scott A. Mardis;Martin Krallinger;Gianni Cesareni;Lynette A. Hirschman;Alfonso Valencia
Affiliations:
Spanish National Cancer Research Centre (CNIO), Madrid;MITRE Corporation, Bedford;Spanish National Cancer Research Centre (CNIO), Madrid;University of Rome Tor Vergata, Rome;MITRE Corporation, Bedford;Spanish National Cancer Research Centre (CNIO), Madrid
Venue:
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Year:
2010

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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.