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

Hong-Jie Dai, Johnny C hi Yang Wu, Wei San Lin, Aaron J ames F Reyes, Mira A nne C Dela Rosa, Shabbir Syed-Abdul, Richard T zong Han Tsai, Wen Lian Hsu

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

UNLABELLED: 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/

Original languageEnglish
JournalDatabase : the journal of biological databases and curation
Volume2014
DOIs
Publication statusPublished - 2014

Fingerprint

Data Mining
liver neoplasms
Biomarkers
Liver Neoplasms
Tumor Biomarkers
Liver
biomarkers
PubMed
browsing
Websites
Genes
Narration
Biological Phenomena
user interface
Biomolecules
MicroRNAs
biomedical research
Human Body
User interfaces
methodology

ASJC Scopus subject areas

  • Medicine(all)

Cite this

LiverCancerMarkerRIF : a liver cancer biomarker interactive curation system combining text mining and expert annotations. / Dai, Hong-Jie; Wu, Johnny C hi Yang; Lin, Wei San; Reyes, Aaron J ames F; Dela Rosa, Mira A nne C; Syed-Abdul, Shabbir; Tsai, Richard T zong Han; Hsu, Wen Lian.

In: Database : the journal of biological databases and curation, Vol. 2014, 2014.

Research output: Contribution to journalArticle

Dai, Hong-Jie ; Wu, Johnny C hi Yang ; Lin, Wei San ; Reyes, Aaron J ames F ; Dela Rosa, Mira A nne C ; Syed-Abdul, Shabbir ; Tsai, Richard T zong Han ; Hsu, Wen Lian. / LiverCancerMarkerRIF : a liver cancer biomarker interactive curation system combining text mining and expert annotations. In: Database : the journal of biological databases and curation. 2014 ; Vol. 2014.
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abstract = "UNLABELLED: 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/",
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