Knowledge-Driven, Data-Assisted Integrative Pathway Analytics

P. Reddy, Stuart Murray, W. Liu
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引用次数: 2

Abstract

Target and biomarker selection in drug discovery relies extensively on the use of various genomics platforms. These technologies generate large amounts of data that can be used to gain novel insights in biology. There is a strong need to mine these information-rich datasets in an effective and efficient manner. Pathway and network based approaches have become an increasingly important methodology to mine bioinformatics datasets derived from ‘omics’ technologies. These approaches also find use in exploring the unknown biology of a disease or functional process. This chapter provides an overview of pathway databases and network tools, network architecture, text mining and existing methods used in knowledge-driven data analysis. It shows examples of how these databases and tools can be used integratively to apply existing knowledge and network-based approach in data analytics.
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知识驱动、数据辅助的综合路径分析
药物发现中的靶标和生物标志物选择广泛依赖于各种基因组学平台的使用。这些技术产生了大量的数据,可以用来获得生物学上的新见解。迫切需要以有效和高效的方式挖掘这些信息丰富的数据集。基于途径和网络的方法已经成为挖掘来自“组学”技术的生物信息学数据集的越来越重要的方法。这些方法也可用于探索未知的疾病生物学或功能过程。本章概述了路径数据库和网络工具、网络架构、文本挖掘和知识驱动数据分析中使用的现有方法。它展示了如何将这些数据库和工具集成起来,在数据分析中应用现有知识和基于网络的方法的示例。
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