# Stochastic Modeling in Systems Biology

Source: [Stochastic Modeling in Systems Biology](<https://www.sota2.com/research/paper/68fa5ea21e209131ce9e3f6b>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-25T18:54:48.646Z

Authors: Jinzhi Lei

Published: 2011-04-23T01:41:18.000Z

## Abstract

Many cellular behaviors are regulated by gene regulation networks, kinetics of which is one of the main subjects in the study of systems biology. Because of the low number molecules in these reacting systems, stochastic effects are significant. In recent years, stochasticity in modeling the kinetics of gene regulation networks have been drawing the attention of many researchers. This paper is a self contained review trying to provide an overview of stochastic modeling. I will introduce the derivation of the main equations in modeling the biochemical systems with intrinsic noise (chemical master equation, Fokker-Plan equation, reaction rate equation, chemical Langevin equation), and will discuss the relations between these formulations. The mathematical formulations for systems with fluctuations in kinetic parameters are also discussed. Finally, I will introduce the exact stochastic simulation algorithm and the approximate explicit tau-leaping method for making numerical simulations.

## Recorded benchmark results

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## Original sources and implementation

[Original paper](<https://arxiv.org/abs/1104.4524>)

[PDF](<https://arxiv.org/pdf/1104.4524.pdf>)