Quantitative mechanistic models based on reaction networks with stochastic chemical kinetics can help elucidate fundamental biological process where random fluctuations are relevant , such as in single cells. The dynamics of such models is described by the master equation , which provides the time course evolution of the probability distribution across the discrete state space consisting of vectors of population levels of the interacting biochemical species.
<coherence> Quantitative mechanistic models based on reaction networks with stochastic chemical kinetics can help elucidate fundamental biological process where random fluctuations are relevant , such as in single cells. The dynamics of such models is described by the master equation , which provides the time course evolution of the probability distribution across the discrete state space consisting of vectors of population levels of the interacting biochemical species.
Quantitative mechanistic models based on reaction networks with stochastic chemical kinetics can help elucidate fundamental biological process where random fluctuations are relevant . The master equation provides the evolution of the probability distribution across the discrete state space consisting of vectors of population levels of the interacting biochemical species.