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Database (Oxford). 2014 Aug 27;2014. pii: bau085. doi: 10.1093/database/bau085. Print 2014.

LiverCancerMarkerRIF: a liver cancer biomarker interactive curation system combining text mining and expert annotations.

Author information

1
Graduate Institute of BioMedical Informatics, College of Medical Science and Technology, Taipei Medical University, 250 Wu-Xin Street, Taipei, Taiwan 110, Republic of China, Institute of Information Science, Academia Sinica, 128 Academia Road, Section 2, Nankang, Taipei, Taiwan 115, Republic of China, Institute of Chemistry, Academia Sinica, 128 Academia Road, Section 2, Nankang, Taipei, Taiwan 115, Republic of China and Department of Computer Science and Information Engineering, National Central University, 300, Jhongda Road, Jhongli City, Taoyuan County, Taiwan 320, Republic of China hjdai@tmu.edu.tw.
2
Graduate Institute of BioMedical Informatics, College of Medical Science and Technology, Taipei Medical University, 250 Wu-Xin Street, Taipei, Taiwan 110, Republic of China, Institute of Information Science, Academia Sinica, 128 Academia Road, Section 2, Nankang, Taipei, Taiwan 115, Republic of China, Institute of Chemistry, Academia Sinica, 128 Academia Road, Section 2, Nankang, Taipei, Taiwan 115, Republic of China and Department of Computer Science and Information Engineering, National Central University, 300, Jhongda Road, Jhongli City, Taoyuan County, Taiwan 320, Republic of China.

Abstract

Biomarkers are biomolecules in the human body that can indicate disease states and abnormal biological processes. Biomarkers are often used during clinical trials to identify patients with cancers. Although biomedical research related to biomarkers has increased over the years and substantial effort has been expended to obtain results in these studies, the specific results obtained often contain ambiguities, and the results might contradict each other. Therefore, the information gathered from these studies must be appropriately integrated and organized to facilitate experimentation on biomarkers. In this study, we used liver cancer as the target and developed a text-mining-based curation system named LiverCancerMarkerRIF, which allows users to retrieve biomarker-related narrations and curators to curate supporting evidence on liver cancer biomarkers directly while browsing PubMed. In contrast to most of the other curation tools that require curators to navigate away from PubMed and accommodate distinct user interfaces or Web sites to complete the curation process, our system provides a user-friendly method for accessing text-mining-aided information and a concise interface to assist curators while they remain at the PubMed Web site. Biomedical text-mining techniques are applied to automatically recognize biomedical concepts such as genes, microRNA, diseases and investigative technologies, which can be used to evaluate the potential of a certain gene as a biomarker. Through the participation in the BioCreative IV user-interactive task, we examined the feasibility of using this novel type of augmented browsing-based curation method, and collaborated with curators to curate biomarker evidential sentences related to liver cancer. The positive feedback received from curators indicates that the proposed method can be effectively used for curation. A publicly available online database containing all the aforementioned information has been constructed at http://btm.tmu.edu.tw/livercancermarkerrif in an attempt to facilitate biomarker-related studies.

DATABASE URL:

http://btm.tmu.edu.tw/LiverCancerMarkerRIF/

PMID:
25168057
PMCID:
PMC4147259
DOI:
10.1093/database/bau085
[Indexed for MEDLINE]
Free PMC Article

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