信息信息学:不再只适用于序列

Donald G. Jackson , Matthew D. Healy1 , Daniel B. Davison
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引用次数: 3

摘要

基因组信息的扩展使得数据整合在生物信息学中与计算分析一样重要。理解药物靶点的“系统生物学”方法需要整合不同类型的数据,包括核苷酸和蛋白质序列、mRNA和蛋白质表达测量、模式生物数据、选择性剪接、单核苷酸多态性(snp)等。这篇综述描述了公开可用的数据库和数据格式如何促进这种集成。然而,这个讨论绝不是全面的。它代表了百时美施贵宝(BMS)生物信息学选择追求的工具和方法。在BMS,有两个工具提供对这些信息的访问。基因组浏览器提供基于序列的信息的图形概述,而药物靶点信息的策划数据库提供注释和分析。所有这些功能的集成为药物发现提供了一个灵活的生物信息学基础设施。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Binformatics: not just for sequences anymore

The expansion of genomic information has made data integration as important to bioinformatics as computational analyses. A ‘systems biology’ approach to understanding drug targets requires integrating diverse types of data, including nucleotide and protein sequences, mRNA and protein expression measurements, model organism data, alternative splicing, single nucleotide polymorphisms (SNPs) and more. This review describes how publicly available databases and data formats facilitate such integration. However, this discussion is by no means comprehensive. It represents the tools and approaches that Bristol-Myers Squibb (BMS) Bioinformatics has chosen to pursue. At BMS, two tools provide access to this information. Genome browsers provide graphic overviews of sequence-based information, whereas a curated database of drug target information provides annotation and analyses. The integration of all these functions results in a flexible bioinformatics infrastructure for drug discovery.

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