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| Content Provider | ACM Digital Library |
|---|---|
| Author | Leitner, Florian Hirschman, Lynette A. Valencia, Alfonso Mardis, Scott A. Krallinger, Martin Cesareni, Gianni |
| 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. |
| Starting Page | 385 |
| Ending Page | 399 |
| Page Count | 15 |
| File Format | |
| ISSN | 15455963 |
| DOI | 10.1109/TCBB.2010.61 |
| Volume Number | 7 |
| Issue Number | 3 |
| Journal | IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB) |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2010-07-01 |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Text mining, text analysis, natural language processing, molecular biology, biological curation. |
| Content Type | Text |
| Resource Type | Article |
| Subject | Genetics Biotechnology Applied Mathematics |
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