Knowledge-Driven, Data-Assisted Integrative Pathway Analytics

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Author(s): Padmalatha S. Reddy (Pfizer, USA), Stuart Murray (Agios Pharmaceuticals Inc, USA)and Wei Liu (Agios Pharmaceuticals Inc, USA)
Copyright: 2011
Pages: 23
Source title: Handbook of Research on Computational and Systems Biology: Interdisciplinary Applications
Source Author(s)/Editor(s): Limin Angela Liu (Shanghai Jiao Tong University, China), Dongqing Wei (Shanghai Jiao Tong University, China), Yixue Li (Shanghai Jiao Tong University, China)and Huimin Lei (Shanghai Jiao Tong University, China)
DOI: 10.4018/978-1-60960-491-2.ch010

Keywords: Bioinformatics / Biologically-Inspired Computing / Medical Information Science Reference / Medicine & Healthcare

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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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Knowledge-Driven, Data-Assisted Integrative Pathway Analytics

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