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Database Profile

LiverCancerMarkerRIF

General information

URL: http://btm.tmu.edu.tw/LiverCancerMarkerRIF/
Full name:
Description: LiverCancerMarkerRIF collects a liver cancer biomarker interactive curation system combining text mining and expert annotations.
Year founded: 2014
Last update: 2014-08-27
Version: v1.0
Accessibility:
Accessible
Country/Region: China

Classification & Tag

Data type:
DNA
Data object:
Database category:
Major species:
Keywords:

Contact information

University/Institution: Taipei Medical University
Address: 250 Wu-Xin Street,Taipei,Taiwan 110,Republic of China
City: Taipei
Province/State: Taiwan
Country/Region: China
Contact name (PI/Team): Hong-Jie Dai
Contact email (PI/Helpdesk): hjdai@tmu.edu.tw

Publications

25168057
LiverCancerMarkerRIF: a liver cancer biomarker interactive curation system combining text mining and expert annotations. [PMID: 25168057]
Dai HJ, Wu JC, Lin WS, Reyes AJ, Dela Rosa MA, Syed-Abdul S, Tsai RT, Hsu WL.

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/ © The Author(s) 2014. Published by Oxford University Press.

Database (Oxford). 2014:2014() | 11 Citations (from Europe PMC, 2026-04-11)

Ranking

All databases:
5327/6932 (23.168%)
5327
Total Rank
11
Citations
0.917
z-index

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Record metadata

Created on: 2015-06-20
Curated by:
Chunlei Yu [2016-04-17]
Chunlei Yu [2016-04-01]
Chunlei Yu [2015-11-20]
Chunlei Yu [2015-06-29]