Models of biochemical systems with few copies of molecules should be stochastic and should account for the random interplay among networks. Despite mathematical tools to account for low-level intrinsic fluctuations are well-known, less is known about the modeling of interplay, especially in biology. Classical abstractions use extrinsic unbounded gaussian noises to model these interplays. However, recent literature showed that bounded noises are a more realistic abstraction. NOISYSIM is a JAVA library to simulate chemically reacting systems where both intrinsic stochasticity and extrinsic bounded noises are present. Intrinsic low-numbers fluctuations are accounted by a Gillespie-like approach, extrinsic noises are modeled as Langevin stochastic equations affecting the model jump rates. NOISYSIM allows to approximate the solution of the Chapman-Kolgomorov equation characterizing the system, thus allowing to asses whether biochemical noise plays a functional role for a target network.

NoisySim: Exact simulation of stochastic chemically reacting systems with extrinsic bounded noises (WIP)

Caravagna G.;D'Onofrio A.;
2013-01-01

Abstract

Models of biochemical systems with few copies of molecules should be stochastic and should account for the random interplay among networks. Despite mathematical tools to account for low-level intrinsic fluctuations are well-known, less is known about the modeling of interplay, especially in biology. Classical abstractions use extrinsic unbounded gaussian noises to model these interplays. However, recent literature showed that bounded noises are a more realistic abstraction. NOISYSIM is a JAVA library to simulate chemically reacting systems where both intrinsic stochasticity and extrinsic bounded noises are present. Intrinsic low-numbers fluctuations are accounted by a Gillespie-like approach, extrinsic noises are modeled as Langevin stochastic equations affecting the model jump rates. NOISYSIM allows to approximate the solution of the Chapman-Kolgomorov equation characterizing the system, thus allowing to asses whether biochemical noise plays a functional role for a target network.
2013
978-1-62748-032-1
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11368/3029132
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