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Overview of the Cancer Genetics and Pathway Curation Tasks of BioNLP Shared Task 2013

Overview
Publisher Biomed Central
Specialty Biology
Date 2015 Jul 24
PMID 26202570
Citations 30
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Abstract

Background: Since their introduction in 2009, the BioNLP Shared Task events have been instrumental in advancing the development of methods and resources for the automatic extraction of information from the biomedical literature. In this paper, we present the Cancer Genetics (CG) and Pathway Curation (PC) tasks, two event extraction tasks introduced in the BioNLP Shared Task 2013. The CG task focuses on cancer, emphasizing the extraction of physiological and pathological processes at various levels of biological organization, and the PC task targets reactions relevant to the development of biomolecular pathway models, defining its extraction targets on the basis of established pathway representations and ontologies.

Results: Six groups participated in the CG task and two groups in the PC task, together applying a wide range of extraction approaches including both established state-of-the-art systems and newly introduced extraction methods. The best-performing systems achieved F-scores of 55% on the CG task and 53% on the PC task, demonstrating a level of performance comparable to the best results achieved in similar previously proposed tasks.

Conclusions: The results indicate that existing event extraction technology can generalize to meet the novel challenges represented by the CG and PC task settings, suggesting that extraction methods are capable of supporting the construction of knowledge bases on the molecular mechanisms of cancer and the curation of biomolecular pathway models. The CG and PC tasks continue as open challenges for all interested parties, with data, tools and resources available from the shared task homepage.

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References
1.
Kitano H . Systems biology: a brief overview. Science. 2002; 295(5560):1662-4. DOI: 10.1126/science.1069492. View

2.
Miwa M, Ohta T, Rak R, Rowley A, Kell D, Pyysalo S . A method for integrating and ranking the evidence for biochemical pathways by mining reactions from text. Bioinformatics. 2013; 29(13):i44-52. PMC: 3694679. DOI: 10.1093/bioinformatics/btt227. View

3.
Oda K, Kim J, Ohta T, Okanohara D, Matsuzaki T, Tateisi Y . New challenges for text mining: mapping between text and manually curated pathways. BMC Bioinformatics. 2008; 9 Suppl 3:S5. PMC: 2352872. DOI: 10.1186/1471-2105-9-S3-S5. View

4.
Finn R, Mistry J, Tate J, Coggill P, Heger A, Pollington J . The Pfam protein families database. Nucleic Acids Res. 2009; 38(Database issue):D211-22. PMC: 2808889. DOI: 10.1093/nar/gkp985. View

5.
Courtot M, Juty N, Knupfer C, Waltemath D, Zhukova A, Drager A . Controlled vocabularies and semantics in systems biology. Mol Syst Biol. 2011; 7:543. PMC: 3261705. DOI: 10.1038/msb.2011.77. View