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The Markyt visualisation, prediction and benchmark platform for chemical and gene entity recognition at BioCreative/CHEMDNER challenge

Biomedical text mining methods and technologies have improved significantly in the last decade. Considerable efforts have been invested in understanding the main challenges of biomedical literature retrieval and extraction and proposing solutions to problems of practical interest. Most notably, comm...

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Autores principales: Pérez-Pérez, Martin, Pérez-Rodríguez, Gael, Rabal, Obdulia, Vazquez, Miguel, Oyarzabal, Julen, Fdez-Riverola, Florentino, Valencia, Alfonso, Krallinger, Martin, Lourenço, Anália
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5001550/
https://www.ncbi.nlm.nih.gov/pubmed/27542845
http://dx.doi.org/10.1093/database/baw120
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author Pérez-Pérez, Martin
Pérez-Rodríguez, Gael
Rabal, Obdulia
Vazquez, Miguel
Oyarzabal, Julen
Fdez-Riverola, Florentino
Valencia, Alfonso
Krallinger, Martin
Lourenço, Anália
author_facet Pérez-Pérez, Martin
Pérez-Rodríguez, Gael
Rabal, Obdulia
Vazquez, Miguel
Oyarzabal, Julen
Fdez-Riverola, Florentino
Valencia, Alfonso
Krallinger, Martin
Lourenço, Anália
author_sort Pérez-Pérez, Martin
collection PubMed
description Biomedical text mining methods and technologies have improved significantly in the last decade. Considerable efforts have been invested in understanding the main challenges of biomedical literature retrieval and extraction and proposing solutions to problems of practical interest. Most notably, community-oriented initiatives such as the BioCreative challenge have enabled controlled environments for the comparison of automatic systems while pursuing practical biomedical tasks. Under this scenario, the present work describes the Markyt Web-based document curation platform, which has been implemented to support the visualisation, prediction and benchmark of chemical and gene mention annotations at BioCreative/CHEMDNER challenge. Creating this platform is an important step for the systematic and public evaluation of automatic prediction systems and the reusability of the knowledge compiled for the challenge. Markyt was not only critical to support the manual annotation and annotation revision process but also facilitated the comparative visualisation of automated results against the manually generated Gold Standard annotations and comparative assessment of generated results. We expect that future biomedical text mining challenges and the text mining community may benefit from the Markyt platform to better explore and interpret annotations and improve automatic system predictions. Database URL: http://www.markyt.org, https://github.com/sing-group/Markyt
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spelling pubmed-50015502016-12-07 The Markyt visualisation, prediction and benchmark platform for chemical and gene entity recognition at BioCreative/CHEMDNER challenge Pérez-Pérez, Martin Pérez-Rodríguez, Gael Rabal, Obdulia Vazquez, Miguel Oyarzabal, Julen Fdez-Riverola, Florentino Valencia, Alfonso Krallinger, Martin Lourenço, Anália Database (Oxford) Original Article Biomedical text mining methods and technologies have improved significantly in the last decade. Considerable efforts have been invested in understanding the main challenges of biomedical literature retrieval and extraction and proposing solutions to problems of practical interest. Most notably, community-oriented initiatives such as the BioCreative challenge have enabled controlled environments for the comparison of automatic systems while pursuing practical biomedical tasks. Under this scenario, the present work describes the Markyt Web-based document curation platform, which has been implemented to support the visualisation, prediction and benchmark of chemical and gene mention annotations at BioCreative/CHEMDNER challenge. Creating this platform is an important step for the systematic and public evaluation of automatic prediction systems and the reusability of the knowledge compiled for the challenge. Markyt was not only critical to support the manual annotation and annotation revision process but also facilitated the comparative visualisation of automated results against the manually generated Gold Standard annotations and comparative assessment of generated results. We expect that future biomedical text mining challenges and the text mining community may benefit from the Markyt platform to better explore and interpret annotations and improve automatic system predictions. Database URL: http://www.markyt.org, https://github.com/sing-group/Markyt Oxford University Press 2016-08-19 /pmc/articles/PMC5001550/ /pubmed/27542845 http://dx.doi.org/10.1093/database/baw120 Text en © The Author(s) 2016. Published by Oxford University Press. http://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/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Pérez-Pérez, Martin
Pérez-Rodríguez, Gael
Rabal, Obdulia
Vazquez, Miguel
Oyarzabal, Julen
Fdez-Riverola, Florentino
Valencia, Alfonso
Krallinger, Martin
Lourenço, Anália
The Markyt visualisation, prediction and benchmark platform for chemical and gene entity recognition at BioCreative/CHEMDNER challenge
title The Markyt visualisation, prediction and benchmark platform for chemical and gene entity recognition at BioCreative/CHEMDNER challenge
title_full The Markyt visualisation, prediction and benchmark platform for chemical and gene entity recognition at BioCreative/CHEMDNER challenge
title_fullStr The Markyt visualisation, prediction and benchmark platform for chemical and gene entity recognition at BioCreative/CHEMDNER challenge
title_full_unstemmed The Markyt visualisation, prediction and benchmark platform for chemical and gene entity recognition at BioCreative/CHEMDNER challenge
title_short The Markyt visualisation, prediction and benchmark platform for chemical and gene entity recognition at BioCreative/CHEMDNER challenge
title_sort markyt visualisation, prediction and benchmark platform for chemical and gene entity recognition at biocreative/chemdner challenge
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5001550/
https://www.ncbi.nlm.nih.gov/pubmed/27542845
http://dx.doi.org/10.1093/database/baw120
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