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Sci. Signal., 28 July 2009
Vol. 2, Issue 81, p. pe44
[DOI: 10.1126/scisignal.281pe44]

PERSPECTIVES

Understanding Modularity in Molecular Networks Requires Dynamics

Roger P. Alexander1,2,3, Philip M. Kim4,5,6,7, Thierry Emonet1,2,8*, and Mark B. Gerstein1,3,9*

1 Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA.
2 Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT 06520, USA.
3 Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA.
4 Terrence Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON M5S 3E1, Canada.
5 Banting and Best Department of Medical Research, University of Toronto, Toronto, ON M5S 3E1, Canada.
6 Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 3E1, Canada.
7 Department of Computer Science, University of Toronto, Toronto, ON M5S 3E1, Canada.
8 Department of Physics, Yale University, New Haven, CT 06520, USA.
9 Department of Computer Science, Yale University, New Haven, CT 06520, USA.

Abstract: The era of genome sequencing has produced long lists of the molecular parts from which cellular machines are constructed. A fundamental goal in systems biology is to understand how cellular behavior emerges from the interaction in time and space of genetically encoded molecular parts, as well as nongenetically encoded small molecules. Networks provide a natural framework for the organization and quantitative representation of all the available data about molecular interactions. The structural and dynamic properties of molecular networks have been the subject of intense research. Despite major advances, bridging network structure to dynamics—and therefore to behavior—remains challenging. A key concept of modern engineering that recurs in the functional analysis of biological networks is modularity. Most approaches to molecular network analysis rely to some extent on the assumption that molecular networks are modular—that is, they are separable and can be studied to some degree in isolation. We describe recent advances in the analysis of modularity in biological networks, focusing on the increasing realization that a dynamic perspective is essential to grouping molecules into modules and determining their collective function.

* Corresponding authors. E-mail, thierry.emonet{at}yale.edu (T.E.); mark.gerstein{at}yale.edu (M.B.G.)

Citation: R. P. Alexander, P. M. Kim, T. Emonet, M. B. Gerstein, Understanding Modularity in Molecular Networks Requires Dynamics. Sci. Signal. 2, pe44 (2009).

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