Literature DB >> 20709523

Diseases as network perturbations.

Antonio del Sol1, Rudi Balling, Lee Hood, David Galas.   

Abstract

The tremendous amount of the data obtained from the study of complex biological systems changes our view on the pathogenesis of human diseases. Instead of looking at individual components of biological processes, we focus our attention more on the interaction and dynamics of biological systems. A network representation and analysis of the physiology and pathophysiology of biological systems is an effective way to study their complex behavior. Specific perturbations can trigger cascades of failures, which lead to the malfunctioning of cellular networks and as a result to the development of specific diseases. In this review we discuss recent developments in the field of disease network analysis and highlight some of the topics and views that we think are important for understanding network-based disease mechanisms.
Copyright © 2010 Elsevier Ltd. All rights reserved.

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Year:  2010        PMID: 20709523     DOI: 10.1016/j.copbio.2010.07.010

Source DB:  PubMed          Journal:  Curr Opin Biotechnol        ISSN: 0958-1669            Impact factor:   9.740


  62 in total

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Review 4.  Taking Systems Medicine to Heart.

Authors:  Kalliopi Trachana; Rhishikesh Bargaje; Gustavo Glusman; Nathan D Price; Sui Huang; Leroy E Hood
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5.  Delineation of key regulatory elements identifies points of vulnerability in the mitogen-activated signaling network.

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6.  Understanding diseases as increased heterogeneity: a complex network computational framework.

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Review 7.  Structure and dynamics of molecular networks: a novel paradigm of drug discovery: a comprehensive review.

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Journal:  Pharmacol Ther       Date:  2013-02-04       Impact factor: 12.310

8.  Revolutionizing medicine in the 21st century through systems approaches.

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Journal:  Biotechnol J       Date:  2012-07-20       Impact factor: 4.677

9.  The Key Genes of Chronic Pancreatitis which Bridge Chronic Pancreatitis and Pancreatic Cancer Can be Therapeutic Targets.

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Review 10.  Genotype to phenotype via network analysis.

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