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A network view of disease and compound screening

Abstract

The large-scale generation and integration of genomic, proteomic, signalling and metabolomic data are increasingly allowing the construction of complex networks that provide a new framework for understanding the molecular basis of physiological or pathophysiological states. Network-based drug discovery aims to harness this knowledge to investigate and understand the impact of interventions, such as candidate drugs, on the molecular networks that define these states. In this article, we describe how such an approach offers a novel way to understand biology, characterize disease and ultimately develop improved therapies, and discuss the challenges to realizing these goals.

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Figure 1: Aims of network-based drug discovery.
Figure 2: Gene expression signatures of disease.
Figure 3: Integration of data sets to construct models of biological networks.
Figure 4: Procedure for network-based drug discovery.

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Acknowledgements

We are grateful to K. Wagner, A. Shaywitz, J. Shaywitz, and J. Millstein for their careful reading of this manuscript and insightful comments. We thank J. Williams of Merck's Creative Services Department for assistance in generating Fig. 3.

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Correspondence to Eric E. Schadt or David A. Shaywitz.

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E. Schadt and S. Friend are employees of Merck Inc. & Co., and own publicly traded shares of stock in Merck. D. Shaywitz is an employee of The Boston Consulting Group, an international strategy and general management consulting firm with clients in nearly every major industry, including health care.

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Schadt, E., Friend, S. & Shaywitz, D. A network view of disease and compound screening. Nat Rev Drug Discov 8, 286–295 (2009). https://doi.org/10.1038/nrd2826

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