Identifying Dynamical Bottlenecks of Stochastic Transitions in Biochemical Networks

Identifying Dynamical Bottlenecks of Stochastic Transitions in Biochemical Networks

In biochemical networks, identifying key proteins and protein-protein reactions that regulate fluctuation-driven transitions leading to pathological cellular function is an important challenge. Using large deviation theory, we develop a semianalytical method to determine how changes in protein expre...

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Bibliographic Details
Main Authors: Yang, Ming (Contributor), Chakraborty, Arup K. (Contributor), Govern, Christopher C. (Contributor)
Other Authors: Massachusetts Institute of Technology. Department of Biological Engineering (Contributor), Massachusetts Institute of Technology. Department of Chemical Engineering (Contributor), Massachusetts Institute of Technology. Department of Chemistry (Contributor), Ragon Institute of MGH, MIT and Harvard (Contributor)
Format: Article
Language:English
Published: American Physical Society, 2012-05-17T17:40:11Z.
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