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Recent advances of automated methods for searching and extracting genomic variant information from biomedical literature

MOTIVATION: To obtain key information for personalized medicine and cancer research, clinicians and researchers in the biomedical field are in great need of searching genomic variant information from the biomedical literature now than ever before. Due to the various written forms of genomic variants...

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Detalles Bibliográficos
Autores principales: Lee, Kyubum, Wei, Chih-Hsuan, Lu, Zhiyong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8138883/
https://www.ncbi.nlm.nih.gov/pubmed/32770181
http://dx.doi.org/10.1093/bib/bbaa142
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author Lee, Kyubum
Wei, Chih-Hsuan
Lu, Zhiyong
author_facet Lee, Kyubum
Wei, Chih-Hsuan
Lu, Zhiyong
author_sort Lee, Kyubum
collection PubMed
description MOTIVATION: To obtain key information for personalized medicine and cancer research, clinicians and researchers in the biomedical field are in great need of searching genomic variant information from the biomedical literature now than ever before. Due to the various written forms of genomic variants, however, it is difficult to locate the right information from the literature when using a general literature search system. To address the difficulty of locating genomic variant information from the literature, researchers have suggested various solutions based on automated literature-mining techniques. There is, however, no study for summarizing and comparing existing tools for genomic variant literature mining in terms of how to search easily for information in the literature on genomic variants. RESULTS: In this article, we systematically compared currently available genomic variant recognition and normalization tools as well as the literature search engines that adopted these literature-mining techniques. First, we explain the problems that are caused by the use of non-standard formats of genomic variants in the PubMed literature by considering examples from the literature and show the prevalence of the problem. Second, we review literature-mining tools that address the problem by recognizing and normalizing the various forms of genomic variants in the literature and systematically compare them. Third, we present and compare existing literature search engines that are designed for a genomic variant search by using the literature-mining techniques. We expect this work to be helpful for researchers who seek information about genomic variants from the literature, developers who integrate genomic variant information from the literature and beyond.
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spelling pubmed-81388832021-05-25 Recent advances of automated methods for searching and extracting genomic variant information from biomedical literature Lee, Kyubum Wei, Chih-Hsuan Lu, Zhiyong Brief Bioinform Method Review MOTIVATION: To obtain key information for personalized medicine and cancer research, clinicians and researchers in the biomedical field are in great need of searching genomic variant information from the biomedical literature now than ever before. Due to the various written forms of genomic variants, however, it is difficult to locate the right information from the literature when using a general literature search system. To address the difficulty of locating genomic variant information from the literature, researchers have suggested various solutions based on automated literature-mining techniques. There is, however, no study for summarizing and comparing existing tools for genomic variant literature mining in terms of how to search easily for information in the literature on genomic variants. RESULTS: In this article, we systematically compared currently available genomic variant recognition and normalization tools as well as the literature search engines that adopted these literature-mining techniques. First, we explain the problems that are caused by the use of non-standard formats of genomic variants in the PubMed literature by considering examples from the literature and show the prevalence of the problem. Second, we review literature-mining tools that address the problem by recognizing and normalizing the various forms of genomic variants in the literature and systematically compare them. Third, we present and compare existing literature search engines that are designed for a genomic variant search by using the literature-mining techniques. We expect this work to be helpful for researchers who seek information about genomic variants from the literature, developers who integrate genomic variant information from the literature and beyond. Oxford University Press 2020-08-07 /pmc/articles/PMC8138883/ /pubmed/32770181 http://dx.doi.org/10.1093/bib/bbaa142 Text en © The Author(s) 2020. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Method Review
Lee, Kyubum
Wei, Chih-Hsuan
Lu, Zhiyong
Recent advances of automated methods for searching and extracting genomic variant information from biomedical literature
title Recent advances of automated methods for searching and extracting genomic variant information from biomedical literature
title_full Recent advances of automated methods for searching and extracting genomic variant information from biomedical literature
title_fullStr Recent advances of automated methods for searching and extracting genomic variant information from biomedical literature
title_full_unstemmed Recent advances of automated methods for searching and extracting genomic variant information from biomedical literature
title_short Recent advances of automated methods for searching and extracting genomic variant information from biomedical literature
title_sort recent advances of automated methods for searching and extracting genomic variant information from biomedical literature
topic Method Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8138883/
https://www.ncbi.nlm.nih.gov/pubmed/32770181
http://dx.doi.org/10.1093/bib/bbaa142
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