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Sci. Signal., 17 April 2012
Vol. 5, Issue 220, p. re1
[DOI: 10.1126/scisignal.2002961]

REVIEWS

Computational Approaches for Analyzing Information Flow in Biological Networks

Boris Kholodenko1, Michael B. Yaffe2, and Walter Kolch1,3*

1 Systems Biology Ireland, University College Dublin, Belfield, Dublin 4, Ireland.
2 Departments of Biology and Biological Engineering, David H. Koch Institute for Integrative Cancer Research at MIT, Massachusetts Institute of Technology, 77 Massachusetts Avenue, 76-353, Cambridge, MA 02139, USA.
3 Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Belfield, Dublin 4, Ireland.

Abstract: The advancements in "omics" (proteomics, genomics, lipidomics, and metabolomics) technologies have yielded large inventories of genes, transcripts, proteins, and metabolites. The challenge is to find out how these entities work together to regulate the processes by which cells respond to external and internal signals. Mathematical and computational modeling of signaling networks has a key role in this task, and network analysis provides insights into biological systems and has applications for medicine. Here, we review experimental and theoretical progress and future challenges toward this goal. We focus on how networks are reconstructed from data, how these networks are structured to control the flow of biological information, and how the design features of the networks specify biological decisions.

* Corresponding author. E-mail: walter.kolch{at}ucd.ie

Citation: B. Kholodenko, M. B. Yaffe, W. Kolch, Computational Approaches for Analyzing Information Flow in Biological Networks. Sci. Signal. 5, re1 (2012).

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