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2013年生物自然语言处理共享任务的癌症遗传学与通路注释任务概述。

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

作者信息

Pyysalo Sampo, Ohta Tomoko, Rak Rafal, Rowley Andrew, Chun Hong-Woo, Jung Sung-Jae, Choi Sung-Pil, Tsujii Jun'ichi, Ananiadou Sophia

出版信息

BMC Bioinformatics. 2015;16 Suppl 10(Suppl 10):S2. doi: 10.1186/1471-2105-16-S10-S2. Epub 2015 Jul 13.

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.

摘要

背景

自2009年推出以来,生物自然语言处理共享任务活动对推动从生物医学文献中自动提取信息的方法和资源的发展起到了重要作用。在本文中,我们介绍癌症遗传学(CG)和通路编目(PC)任务,这是2013年生物自然语言处理共享任务中引入的两个事件提取任务。CG任务聚焦于癌症,强调在生物组织的各个层面提取生理和病理过程,而PC任务则针对与生物分子通路模型开发相关的反应,基于已建立的通路表示和本体来定义其提取目标。

结果

六组参与了CG任务,两组参与了PC任务,他们共同应用了广泛的提取方法,包括既定的最先进系统和新引入的提取方法。表现最佳的系统在CG任务上的F值为55%,在PC任务上为53%,这表明其性能水平与之前类似任务中取得的最佳结果相当。

结论

结果表明,现有的事件提取技术可以进行推广,以应对由CG和PC任务设置所代表的新挑战,这意味着提取方法能够支持构建关于癌症分子机制的知识库以及生物分子通路模型的编目。CG和PC任务仍然是所有感兴趣方面临的开放性挑战,共享任务主页提供了数据、工具和资源。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/16cc/4511510/8c5df8dde584/1471-2105-16-S10-S2-1.jpg

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