Cargando…
tmVar 3.0: an improved variant concept recognition and normalization tool
MOTIVATION: Previous studies have shown that automated text-mining tools are becoming increasingly important for successfully unlocking variant information in scientific literature at large scale. Despite multiple attempts in the past, existing tools are still of limited recognition scope and precis...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9477515/ https://www.ncbi.nlm.nih.gov/pubmed/35904569 http://dx.doi.org/10.1093/bioinformatics/btac537 |
_version_ | 1784790378343301120 |
---|---|
author | Wei, Chih-Hsuan Allot, Alexis Riehle, Kevin Milosavljevic, Aleksandar Lu, Zhiyong |
author_facet | Wei, Chih-Hsuan Allot, Alexis Riehle, Kevin Milosavljevic, Aleksandar Lu, Zhiyong |
author_sort | Wei, Chih-Hsuan |
collection | PubMed |
description | MOTIVATION: Previous studies have shown that automated text-mining tools are becoming increasingly important for successfully unlocking variant information in scientific literature at large scale. Despite multiple attempts in the past, existing tools are still of limited recognition scope and precision. RESULT: We propose tmVar 3.0: an improved variant recognition and normalization system. Compared to its predecessors, tmVar 3.0 recognizes a wider spectrum of variant-related entities (e.g. allele and copy number variants), and groups together different variant mentions belonging to the same genomic sequence position in an article for improved accuracy. Moreover, tmVar 3.0 provides advanced variant normalization options such as allele-specific identifiers from the ClinGen Allele Registry. tmVar 3.0 exhibits state-of-the-art performance with over 90% in F-measure for variant recognition and normalization, when evaluated on three independent benchmarking datasets. tmVar 3.0 as well as annotations for the entire PubMed and PMC datasets are freely available for download. AVAILABILITY AND IMPLEMENTATION: https://github.com/ncbi/tmVar3 |
format | Online Article Text |
id | pubmed-9477515 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-94775152022-09-19 tmVar 3.0: an improved variant concept recognition and normalization tool Wei, Chih-Hsuan Allot, Alexis Riehle, Kevin Milosavljevic, Aleksandar Lu, Zhiyong Bioinformatics Applications Note MOTIVATION: Previous studies have shown that automated text-mining tools are becoming increasingly important for successfully unlocking variant information in scientific literature at large scale. Despite multiple attempts in the past, existing tools are still of limited recognition scope and precision. RESULT: We propose tmVar 3.0: an improved variant recognition and normalization system. Compared to its predecessors, tmVar 3.0 recognizes a wider spectrum of variant-related entities (e.g. allele and copy number variants), and groups together different variant mentions belonging to the same genomic sequence position in an article for improved accuracy. Moreover, tmVar 3.0 provides advanced variant normalization options such as allele-specific identifiers from the ClinGen Allele Registry. tmVar 3.0 exhibits state-of-the-art performance with over 90% in F-measure for variant recognition and normalization, when evaluated on three independent benchmarking datasets. tmVar 3.0 as well as annotations for the entire PubMed and PMC datasets are freely available for download. AVAILABILITY AND IMPLEMENTATION: https://github.com/ncbi/tmVar3 Oxford University Press 2022-07-29 /pmc/articles/PMC9477515/ /pubmed/35904569 http://dx.doi.org/10.1093/bioinformatics/btac537 Text en © The Author(s) 2022. Published by Oxford University Press. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Applications Note Wei, Chih-Hsuan Allot, Alexis Riehle, Kevin Milosavljevic, Aleksandar Lu, Zhiyong tmVar 3.0: an improved variant concept recognition and normalization tool |
title | tmVar 3.0: an improved variant concept recognition and normalization tool |
title_full | tmVar 3.0: an improved variant concept recognition and normalization tool |
title_fullStr | tmVar 3.0: an improved variant concept recognition and normalization tool |
title_full_unstemmed | tmVar 3.0: an improved variant concept recognition and normalization tool |
title_short | tmVar 3.0: an improved variant concept recognition and normalization tool |
title_sort | tmvar 3.0: an improved variant concept recognition and normalization tool |
topic | Applications Note |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9477515/ https://www.ncbi.nlm.nih.gov/pubmed/35904569 http://dx.doi.org/10.1093/bioinformatics/btac537 |
work_keys_str_mv | AT weichihhsuan tmvar30animprovedvariantconceptrecognitionandnormalizationtool AT allotalexis tmvar30animprovedvariantconceptrecognitionandnormalizationtool AT riehlekevin tmvar30animprovedvariantconceptrecognitionandnormalizationtool AT milosavljevicaleksandar tmvar30animprovedvariantconceptrecognitionandnormalizationtool AT luzhiyong tmvar30animprovedvariantconceptrecognitionandnormalizationtool |