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

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Please use this identifier to cite or link to this item: https://ir.lib.ncu.edu.tw/handle/987654321/106960

Title:	LiverCancerMarkerRIF: a liver cancer biomarker interactive curation system combining text mining and expert annotations
Authors:	蔡宗翰;Dai, H.-J.;Wu, J. C.-Y.;Lin, W.-S.;Reyes, A. J. F.;dela Rosa, M. A. C.;Syed-Abdul, S.;Tsai, R. T.-H.;Hsu, W.-L.
Contributors:	資訊電機學院資訊工程學系
Keywords:	biomarkers;Biomarkers, Tumor;biomedical research;clinical trials;Computational Biology - methods;Data Curation - methods;Data Mining - methods;Database Management Systems;genes;Humans;Internet;Liver Neoplasms;microRNA;Original;patients;User-Computer Interface
Date:	2014-01-01
Issue Date:	2026-04-23 13:50:35 (UTC+8)
Publisher:	Oxford University Press;England: Oxford University Press
Abstract:	摘要： 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. http://btm.tmu.edu.tw/LiverCancerMarkerRIF/ 其他題名： Database (Oxford) 出版者： England: Oxford University Press 出版日期： 2014 出處： Database : the journal of biological databases and curation, 2014, Vol.2014 (p.bau085-bau085), p.bau085-bau085 版權： The Author(s) 2014. Published by Oxford University Press. 版權： The Author(s) 2014. Published by Oxford University Press. 2014 識別號： ISSN: 1758-0463 識別號： EISSN: 1758-0463 識別號： DOI: 10.1093/database/bau085 識別號： PMID: 25168057
Appears in Collections:	[Department of Computer Science and information Engineering] journal & Dissertation

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