Oct 10, 2019 · We convert mathematical ODE models of three benchmark biological systems to Dynamic Bayesian Networks (DBNs). The DBN model can handle model ...

Oct 14, 2019 · Dealing with stochasticity in biological ODE models. In Proceedings of Workshop on Computational Biology (WCB), co-located with 34th ...

Sep 7, 2024 · Expert knowledge in the form of mathematical models can be considered sufficient statistics of all prior experimentation in the domain, ...

We convert mathematical ODE models of three benchmark biological systems to Dynamic Bayesian Networks (DBNs). The DBN model can handle model uncertainty and ...

This chapter is concerned with continuous time processes, which are often modeled as a system of ordinary differential equations (ODEs). These models assume ...

Oct 18, 2023 · Rigorously probing the biology of living cells requires a unified mathematical framework that accounts for single-molecule biological stochasticity.

Dec 18, 2023 · Most deterministic ODE models can be turned into stochastic models via adding a noise term in the dynamics, which changes the qualitative ...

Dec 16, 2020 · We provide an accessible introduction to identifiability analysis and demonstrate how existing ideas for analysis of ODE models can be applied to stochastic ...

Jun 14, 2015 · In this paper, we propose a new stochastic GRN model by investigating incorporation of various standard noise measurements in the deterministic S-system model.

This chapter is concerned with continuous time processes, which are often modeled as a system of ordinary differential equations (ODEs), where relevant ...