BEST: Next-generation biomedical entity search tool for knowledge discovery from biomedical literature

Sunwon Lee, Donghyeon Kim, Kyubum Lee, Jaehoon Choi, Seongsoon Kim, Minji Jeon, Sangrak Lim, Donghee Choi, Sunkyu Kim, Aik-Choon Tan, Jaewoo Kang

Research output: Contribution to journalArticle

22 Citations (Scopus)

Abstract

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preprocess the PubMed corpus to speed up the response time; however, they are not constantly updated, and thus produce outdated results.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-todate results in real time including mutation information in the results. BEST is freely accessible at http://best.korea.ac.kr.

Original languageEnglish
Article numbere0164680
JournalPLoS One
Volume11
Issue number10
DOIs
Publication statusPublished - 2016 Oct 1

Fingerprint

PubMed
Data mining
mutation
Mutation
Reaction Time
Search Engine
drugs
engines
Korea
MicroRNAs
Pharmaceutical Preparations
Korean Peninsula
Publications
Search engines
complement
Transcription Factors
transcription factors
Genes
genes

ASJC Scopus subject areas

  • Medicine(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)

Cite this

BEST : Next-generation biomedical entity search tool for knowledge discovery from biomedical literature. / Lee, Sunwon; Kim, Donghyeon; Lee, Kyubum; Choi, Jaehoon; Kim, Seongsoon; Jeon, Minji; Lim, Sangrak; Choi, Donghee; Kim, Sunkyu; Tan, Aik-Choon; Kang, Jaewoo.

In: PLoS One, Vol. 11, No. 10, e0164680, 01.10.2016.

Research output: Contribution to journalArticle

Lee, S, Kim, D, Lee, K, Choi, J, Kim, S, Jeon, M, Lim, S, Choi, D, Kim, S, Tan, A-C & Kang, J 2016, 'BEST: Next-generation biomedical entity search tool for knowledge discovery from biomedical literature', PLoS One, vol. 11, no. 10, e0164680. https://doi.org/10.1371/journal.pone.0164680
Lee, Sunwon ; Kim, Donghyeon ; Lee, Kyubum ; Choi, Jaehoon ; Kim, Seongsoon ; Jeon, Minji ; Lim, Sangrak ; Choi, Donghee ; Kim, Sunkyu ; Tan, Aik-Choon ; Kang, Jaewoo. / BEST : Next-generation biomedical entity search tool for knowledge discovery from biomedical literature. In: PLoS One. 2016 ; Vol. 11, No. 10.
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