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/
Highlights
Through the participation in the BioCreative IV user-interactive task, we examined the VC The Author(s) 2014
In the case of each data set, a curator was required to extract the following information: PubMed ID (PMID) of the abstract, gene terms and the corresponding gene ID from Entrez Gene, evidential sentences indicating that a gene is a biomarker for liver cancer, and relationship affirmation in the case of the tool-assisted curation
The curators considered the highlighting of biomedical concept names to be extremely helpful and the instructions of LiverCancerMarkerRIF to be simple and clear
Summary
Completing the task resulted in the generation of a database that contains evidential sentences that describe the relationship between biomarkers and liver cancer; this database is available at http://btm.tmu.edu.tw/livercancermarkerrif. When users log on LiverCancerMarkerRIF, a curation interface is made available (Figure 2) that curators can use to curate or modify extracted RIF sentences directly on PubMed. Once they are confirmed, the function-describing sentences are instantly submitted to our database and can be accessed by other users.
Sign-in/Register to view highlights & summary 
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call