Computational systems biology in drug discovery and development: methods and applications

Authored by Wayne Materi, David S. Wishart

Date Published: 2007-04

DOI: 10.1016/j.druidis.2007.02.013

Sponsors: National Institute for Nanotechnology (NINT) National Research Council of Canada (NRC) Genome Alberta

Platforms: No platforms listed

Model Documentation: Other Narrative Flow charts

Model Code URLs: Model code not found

Abstract

Computational systems biology is an emerging field in biological simulation that attempts to model or simulate intra- and intercellular events using data gathered from genomic, proteomic or metabolomic experiments. The need to model complex temporal and spatiotemporal processes at many different scales has led to the emergence of numerous techniques, including systems of differential equations, Petri nets, cellular automata simulators, agent-based models and pi calculus. This review provides a brief summary and an assessment of most of these approaches. It also provides examples of how these methods are being used to facilitate drug discovery and development.

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