HomeAbout

SIGN IN   Advanced Search










 
Browse Illustration
Understanding Modularity in Molecular Networks Requires Dynamics

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.

Rate this Resource:
1 = not useful, 5 = very useful

Please be the first to rate this resource.


Subscribe and
View Resource

Classifications


Resource Type: Bibliography, Diagram, Illustration, Journal article/Issue, Review
Audience Level: Undergraduate upper division 15-16, Graduate, Professional (degree program)

Author and Copyright


Authors and Editors: Roger P. Alexander of Program in Computational Biology and Bioinformatics, Yale University, Philip M. Kim of Terrence Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Thierry Emonet of Program in Computational Biology and Bioinformatics, Yale University, Mark B. Gerstein of Program in Computational Biology and Bioinformatics, Yale University
Publisher: American Association for the Advancement of Science
Format: application/pdf, image/gif, image/jpeg, text/html
Copyright and other restrictions: Yes
Cost: Yes

Comments


» Sign In or register to post comments.


Collection:
STKE/Science Signaling


     
   

SITE MAP | CONTACT | POLICIES

Triple A S National Science Foundation Naitonal Science Digital Library Pathway
Funded by the individual BEN Collaborators and grants from the
National Science Foundation [DUE 0085840 / DUE 0226185 / DUE 0532797 / DUE 0734995]

This website is a National Science Digital Library (NSDL) Pathway.
Copyright © 2019. American Association for the Advancement of Science. All Rights Reserved.