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Bioinformatics in translational drug discovery

Bioinformatics approaches are becoming ever more essential in translational drug discovery both in academia and within the pharmaceutical industry. Computational exploitation of the increasing volumes of data generated during all phases of drug discovery is enabling key challenges of the process to...

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Detalles Bibliográficos
Autores principales: Wooller, Sarah K., Benstead-Hume, Graeme, Chen, Xiangrong, Ali, Yusuf, Pearl, Frances M.G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Portland Press Ltd. 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6448364/
https://www.ncbi.nlm.nih.gov/pubmed/28487472
http://dx.doi.org/10.1042/BSR20160180
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author Wooller, Sarah K.
Benstead-Hume, Graeme
Chen, Xiangrong
Ali, Yusuf
Pearl, Frances M.G.
author_facet Wooller, Sarah K.
Benstead-Hume, Graeme
Chen, Xiangrong
Ali, Yusuf
Pearl, Frances M.G.
author_sort Wooller, Sarah K.
collection PubMed
description Bioinformatics approaches are becoming ever more essential in translational drug discovery both in academia and within the pharmaceutical industry. Computational exploitation of the increasing volumes of data generated during all phases of drug discovery is enabling key challenges of the process to be addressed. Here, we highlight some of the areas in which bioinformatics resources and methods are being developed to support the drug discovery pipeline. These include the creation of large data warehouses, bioinformatics algorithms to analyse ‘big data’ that identify novel drug targets and/or biomarkers, programs to assess the tractability of targets, and prediction of repositioning opportunities that use licensed drugs to treat additional indications.
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spelling pubmed-64483642019-04-16 Bioinformatics in translational drug discovery Wooller, Sarah K. Benstead-Hume, Graeme Chen, Xiangrong Ali, Yusuf Pearl, Frances M.G. Biosci Rep Review Articles Bioinformatics approaches are becoming ever more essential in translational drug discovery both in academia and within the pharmaceutical industry. Computational exploitation of the increasing volumes of data generated during all phases of drug discovery is enabling key challenges of the process to be addressed. Here, we highlight some of the areas in which bioinformatics resources and methods are being developed to support the drug discovery pipeline. These include the creation of large data warehouses, bioinformatics algorithms to analyse ‘big data’ that identify novel drug targets and/or biomarkers, programs to assess the tractability of targets, and prediction of repositioning opportunities that use licensed drugs to treat additional indications. Portland Press Ltd. 2017-07-07 /pmc/articles/PMC6448364/ /pubmed/28487472 http://dx.doi.org/10.1042/BSR20160180 Text en © 2017 The Author(s). http://creativecommons.org/licenses/by/4.0/This is an open access article published by Portland Press Limited on behalf of the Biochemical Society and distributed under the Creative Commons Attribution License 4.0 (CC BY) (http://creativecommons.org/licenses/by/4.0/) .
spellingShingle Review Articles
Wooller, Sarah K.
Benstead-Hume, Graeme
Chen, Xiangrong
Ali, Yusuf
Pearl, Frances M.G.
Bioinformatics in translational drug discovery
title Bioinformatics in translational drug discovery
title_full Bioinformatics in translational drug discovery
title_fullStr Bioinformatics in translational drug discovery
title_full_unstemmed Bioinformatics in translational drug discovery
title_short Bioinformatics in translational drug discovery
title_sort bioinformatics in translational drug discovery
topic Review Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6448364/
https://www.ncbi.nlm.nih.gov/pubmed/28487472
http://dx.doi.org/10.1042/BSR20160180
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