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Bioinformatics in translational drug discovery
Author(s) -
Sarah K. Wooller,
Graeme Benstead-Hume,
Xiangrong Chen,
Yusuf Ali,
Frances M. G. Pearl
Publication year - 2017
Publication title -
bioscience reports
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.938
H-Index - 77
eISSN - 1573-4935
pISSN - 0144-8463
DOI - 10.1042/bsr20160180
Subject(s) - drug discovery , data science , pipeline (software) , computer science , big data , key (lock) , drug repositioning , pharmaceutical industry , process (computing) , computational biology , drug , bioinformatics , data mining , biology , microbiology and biotechnology , pharmacology , computer security , programming language , operating system
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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