Verena Wolf: "Stochastic models of chemical reactions: What's with all the noise?"
Wann |
22.03.2010 von 11:15 bis 12:00 |
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Wo | FRIAS Seminarraum, Albertstr. 19, 79104 Freiburg |
Name | Hauke Busch |
Kontakttelefon | +49 (0)761 203 97154 |
Teilnehmer |
Universitäts öffentlich |
Termin übernehmen |
vCal iCal |
Dr. Verena Wolf
Computer Science Department, Saarland University
Stochastic models of chemical reactions: What's with all the noise?
Within systems biology there is an increasing interest in the stochastic behavior of biochemical reaction networks. An appropriate stochastic description is provided by the chemical master equation (CME), which describes a continuous-time discrete-state Markov process. In this process we count for each chemical species the (discrete) number of molecules that are currently present in system and assume that chemical reactions occur after random delays.
In the first part of my talk I will present the main benefits of the stochastic approach and explain when a stochastic model is necessary and when not.
The second part will be devoted to recent advances in computational approaches to solve the CME. In particular, I will discuss the computation of probabilities of certain events (e.g. the probability that a certain cellular decision is taken), the probability distribution of the time until a certain event occurs (e.g. the time to switch in a bistable system from one stable region to another), or the probability that the population of a chemical species reaches a certain threshold.
The main hurdle in computing these quantities is that the state space of the underlying Markov process can be very large. Even if suitable truncations of the state space are found, a numerical solution may become impossible since too many states have to be considered.
In the third and final part of my presentation, I will conclude with a discussion about hybrid approaches where the population of certain chemical species are represented is as a continuous deterministic variable and other populations as discrete random variables.