Optimal variational perturbations for the inference of stochastic reaction dynamics

2012 IEEE 51st IEEE Conference on Decision and Control (CDC) ◽

10.1109/cdc.2012.6426738 ◽

2012 ◽

Cited By ~ 2

Author(s):

C. Zechner ◽

P. Nandy ◽

M. Unger ◽

H. Koeppl

Keyword(s):

Reaction Dynamics ◽

Variational Perturbations ◽

Stochastic Reaction

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Noise and delay can shape distribution functions in stochastic reaction dynamics

Nonlinear Dynamics ◽

10.1007/s11071-021-06643-5 ◽

2021 ◽

Author(s):

Jyoti Bhadana ◽

Athokpam Langlen Chanu ◽

Md. Zubbair Malik ◽

R. K. Brojen Singh

Keyword(s):

Reaction Dynamics ◽

Distribution Functions ◽

Shape Distribution ◽

Stochastic Reaction

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Stochastic reaction networks in dynamic compartment populations

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.2003734117 ◽

2020 ◽

Vol 117 (37) ◽

pp. 22674-22683

Author(s):

Lorenzo Duso ◽

Christoph Zechner

Keyword(s):

Biological Systems ◽

Reaction Dynamics ◽

Theoretical Models ◽

Counting Processes ◽

Mathematical Framework ◽

Biological Processes ◽

Biochemical Processes ◽

Subcellular Compartmentalization ◽

Stochastic Reaction ◽

Stochastic Reaction Networks

Compartmentalization of biochemical processes underlies all biological systems, from the organelle to the tissue scale. Theoretical models to study the interplay between noisy reaction dynamics and compartmentalization are sparse, and typically very challenging to analyze computationally. Recent studies have made progress toward addressing this problem in the context of specific biological systems, but a general and sufficiently effective approach remains lacking. In this work, we propose a mathematical framework based on counting processes that allows us to study dynamic compartment populations with arbitrary interactions and internal biochemistry. We derive an efficient description of the dynamics in terms of differential equations which capture the statistics of the population. We demonstrate the relevance of our approach by analyzing models inspired by different biological processes, including subcellular compartmentalization and tissue homeostasis.

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