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Literature evidence in open targets - a target validation platform

BACKGROUND: We present the Europe PMC literature component of Open Targets - a target validation platform that integrates various evidence to aid drug target identification and validation. The component identifies target-disease associations in documents and ranks the documents based on their confid...

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Detalles Bibliográficos
Autores principales: Kafkas, Şenay, Dunham, Ian, McEntyre, Johanna
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5461726/
https://www.ncbi.nlm.nih.gov/pubmed/28587637
http://dx.doi.org/10.1186/s13326-017-0131-3
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author Kafkas, Şenay
Dunham, Ian
McEntyre, Johanna
author_facet Kafkas, Şenay
Dunham, Ian
McEntyre, Johanna
author_sort Kafkas, Şenay
collection PubMed
description BACKGROUND: We present the Europe PMC literature component of Open Targets - a target validation platform that integrates various evidence to aid drug target identification and validation. The component identifies target-disease associations in documents and ranks the documents based on their confidence from the Europe PMC literature database, by using rules utilising expert-provided heuristic information. The confidence score of a given document represents how valuable the document is in the scope of target validation for a given target-disease association by taking into account the credibility of the association based on the properties of the text. The component serves the platform regularly with the up-to-date data since December, 2015. RESULTS: Currently, there are a total number of 1168365 distinct target-disease associations text mined from >26 million PubMed abstracts and >1.2 million Open Access full text articles. Our comparative analyses on the current available evidence data in the platform revealed that 850179 of these associations are exclusively identified by literature mining. CONCLUSIONS: This component helps the platform’s users by providing the most relevant literature hits for a given target and disease. The text mining evidence along with the other types of evidence can be explored visually through https://www.targetvalidation.org and all the evidence data is available for download in json format from https://www.targetvalidation.org/downloads/data.
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spelling pubmed-54617262017-06-07 Literature evidence in open targets - a target validation platform Kafkas, Şenay Dunham, Ian McEntyre, Johanna J Biomed Semantics Software BACKGROUND: We present the Europe PMC literature component of Open Targets - a target validation platform that integrates various evidence to aid drug target identification and validation. The component identifies target-disease associations in documents and ranks the documents based on their confidence from the Europe PMC literature database, by using rules utilising expert-provided heuristic information. The confidence score of a given document represents how valuable the document is in the scope of target validation for a given target-disease association by taking into account the credibility of the association based on the properties of the text. The component serves the platform regularly with the up-to-date data since December, 2015. RESULTS: Currently, there are a total number of 1168365 distinct target-disease associations text mined from >26 million PubMed abstracts and >1.2 million Open Access full text articles. Our comparative analyses on the current available evidence data in the platform revealed that 850179 of these associations are exclusively identified by literature mining. CONCLUSIONS: This component helps the platform’s users by providing the most relevant literature hits for a given target and disease. The text mining evidence along with the other types of evidence can be explored visually through https://www.targetvalidation.org and all the evidence data is available for download in json format from https://www.targetvalidation.org/downloads/data. BioMed Central 2017-06-06 /pmc/articles/PMC5461726/ /pubmed/28587637 http://dx.doi.org/10.1186/s13326-017-0131-3 Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Software
Kafkas, Şenay
Dunham, Ian
McEntyre, Johanna
Literature evidence in open targets - a target validation platform
title Literature evidence in open targets - a target validation platform
title_full Literature evidence in open targets - a target validation platform
title_fullStr Literature evidence in open targets - a target validation platform
title_full_unstemmed Literature evidence in open targets - a target validation platform
title_short Literature evidence in open targets - a target validation platform
title_sort literature evidence in open targets - a target validation platform
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5461726/
https://www.ncbi.nlm.nih.gov/pubmed/28587637
http://dx.doi.org/10.1186/s13326-017-0131-3
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