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

BMC Bioinformatics

Research

Sampo Pyysalo¹  Sung-Pil Choi²  Jun'ichi Tsujii³  Rafal Rak⁴  Sophia Ananiadou⁴  Andrew Rowley⁴  Hong-Woo Chun⁵  Sung-Jae Jung⁶  Tomoko Ohta⁷ 

[1] Department of Information technology, University of Turku, Turku, Finland;Department of Library and Information Science, Kyonggi University, Suwon, South Korea;Microsoft Research Asia, Beijing, China;National Centre for Text Mining and School of Computer Science, University of Manchester, Manchester, UK;Software Research Center, Korea Institute of Science and Technology Information (KISTI), Daejeon, South Korea;Software Research Center, Korea Institute of Science and Technology Information (KISTI), Daejeon, South Korea;Department of Applied Information Science, University of Science and Technology (UST), Daejeon, South Korea;textimi, Tokyo, Japan;

关键词: Cancer Genetic;    Event Extraction;    System Biology Markup Language;    Anatomical Entity;    Entity Annotation;   

DOI  :  10.1186/1471-2105-16-S10-S2

来源: Springer

【 摘 要 】

BackgroundSince 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.ResultsSix 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.ConclusionsThe 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.

【 授权许可】

CC BY   
© Pyysalo et al.; licensee BioMed Central Ltd. 2015