Unknown

Dataset Information

0

Identifying dynamical bottlenecks of stochastic transitions in biochemical networks.


ABSTRACT: 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 expression and rate parameters of protein-protein reactions influence the rate of such transitions. Our formulas agree well with computationally costly direct simulations and are consistent with experiments. Our approach reveals qualitative features of key reactions that regulate stochastic transitions.

SUBMITTER: Govern CC 

PROVIDER: S-EPMC5470593 | biostudies-literature | 2012 Feb

REPOSITORIES: biostudies-literature

altmetric image

Publications

Identifying dynamical bottlenecks of stochastic transitions in biochemical networks.

Govern Christopher C CC   Yang Ming M   Chakraborty Arup K AK  

Physical review letters 20120130 5


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 expression and rate parameters of protein-protein reactions influence the rate of such transitions. Our formulas agree well with computationally costly direct simulations and are consistent with experiment  ...[more]

Similar Datasets

| S-EPMC6301693 | biostudies-literature
| S-EPMC3400272 | biostudies-literature
| S-EPMC2034356 | biostudies-literature
| S-EPMC2705573 | biostudies-literature
| S-EPMC4673532 | biostudies-literature
| S-EPMC3324259 | biostudies-other
| S-EPMC2898671 | biostudies-literature
| S-EPMC5481150 | biostudies-literature
| S-EPMC3517980 | biostudies-literature