BEST: Next-Generation Biomedical Entity Search Tool for Knowledge Discovery from Biomedical Literature

As the volume of publications rapidly increases, searching for relevant information from the literature becomes more challenging. To complement standard search engines such as PubMed, it is desirable to have an advanced search tool that directly returns relevant biomedical entities such as targets,...

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Bibliographic Details
Published in:PloS one 2016-10, Vol.11 (10), p.e0164680-e0164680
Main Authors: Lee, Sunwon, Kim, Donghyeon, Lee, Kyubum, Choi, Jaehoon, Kim, Seongsoon, Jeon, Minji, Lim, Sangrak, Choi, Donghee, Kim, Sunkyu, Tan, Aik-Choon, Kang, Jaewoo
Format: Article
Language:English
Subjects:
Bioinformatics
Biology and Life Sciences
Biomedical Research
Computer science
Data Mining - methods
Dictionaries
DNA binding proteins
Drug Resistance - genetics
Drugs
Engineering
Genes
Information processing
Kinases
Knowledge discovery
Leukemia
Medicine and Health Sciences
Metabolites
Mutation
Queries
Query processing
Research and Analysis Methods
Researchers
Response time (computers)
Search engines
Social Sciences
Transcription factors
User-Computer Interface
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Summary:As the volume of publications rapidly increases, searching for relevant information from the literature becomes more challenging. To complement standard search engines such as PubMed, it is desirable to have an advanced search tool that directly returns relevant biomedical entities such as targets, drugs, and mutations rather than a long list of articles. Some existing tools submit a query to PubMed and process retrieved abstracts to extract information at query time, resulting in a slow response time and limited coverage of only a fraction of the PubMed corpus. Other tools preprocess the PubMed corpus to speed up the response time; however, they are not constantly updated, and thus produce outdated results. Further, most existing tools cannot process sophisticated queries such as searches for mutations that co-occur with query terms in the literature. To address these problems, we introduce BEST, a biomedical entity search tool. BEST returns, as a result, a list of 10 different types of biomedical entities including genes, diseases, drugs, targets, transcription factors, miRNAs, and mutations that are relevant to a user's query. To the best of our knowledge, BEST is the only system that processes free text queries and returns up-to-date results in real time including mutation information in the results. BEST is freely accessible at http://best.korea.ac.kr.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0164680