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转化药物研发中的生物信息学

Bioinformatics in translational drug discovery.

作者信息

Wooller Sarah K, Benstead-Hume Graeme, Chen Xiangrong, Ali Yusuf, Pearl Frances M G

机构信息

School of Life Sciences, University of Sussex, Falmer, Brighton BN1 9QJ, U.K.

出版信息

Biosci Rep. 2017 Jul 7;37(4). doi: 10.1042/BSR20160180. Print 2017 Aug 31.

Abstract

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.

摘要

生物信息学方法在学术界和制药行业的转化药物发现中变得越来越重要。对药物发现各阶段产生的大量数据进行计算利用,有助于解决该过程中的关键挑战。在此,我们重点介绍一些正在开发生物信息学资源和方法以支持药物发现流程的领域。这些领域包括创建大型数据仓库、用于分析“大数据”以识别新药物靶点和/或生物标志物的生物信息学算法、评估靶点可处理性的程序,以及利用已获许可药物治疗其他适应症的重新定位机会预测。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d201/6448364/b739cf19f8a9/bsr-37-bsr20160180-g1.jpg

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