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Analytical and Numerical Methods for Stochastic Biological Systems

Topic Information

Dear Colleagues,

Stochastic mathematical models have been recognized as the most effective tools for understanding, analyzing, and predicting the real-world problems that humanity faces every day. These problems are addressed and introduced by researchers working in all fields of applied sciences. Perhaps the major challenge for researchers is the process of mathematical analysis and prediction. To analyze these models, one must solve them numerically or analytically and use the solution to make predictions based on the shape of perturbations and its associated theoretical framework. Due to the complexity of these models, new numerical charts and analysis methods have been developed to solve these models. Generally, this Topics aims to publish original and high-quality research articles covering the new analytical and numerical methods for perturbed real-world biological systems. In this context, continuous and discrete time stochastic processes will be discussed, as well as stochastic differential equations, stochastic partial differential equation, Lévy processes, first-passage-time problems, stochastic optimal control, parameter estimation, and advanced simulation techniques. All the above topics are intended to be treated in the spirit of modeling the evolution of stochastic systems of interest in biology. Potential topics include but are not limited to the following:

  • Stability analysis for stochastic differential equations in biology.
  • Partial differential equation models in biology.
  • Jump-diffusion processes.
  • Markov and semi-Markov processes.
  • Stochastic optimal control.
  • Numerical solutions of stochastic differential equations.
  • Parameter Estimation in stochastic differential equations.

The aim of this Topics is to compile a collection of articles reflecting the latest developments in stochastic modeling in biology, with the aim of studying the qualitative and quantitative behavior of phenomena in which a random component is necessary.

Dr. Mehmet Yavuz
Prof. Dr. Necati Ozdemir
Prof. Dr. Mouhcine Tilioua
Prof. Dr. Yassine Sabbar
Topic Editors

Keywords

  • stochastic differential equations in biology
  • partial differential equation in biology
  • jump-diffusion processes
  • Markov and semi-Markov processes

Participating Journals

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14,168 Articles
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5.2CiteScore
22 DaysMedian Time to First Decision
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3,671 Articles
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3.3Impact Factor
6.0CiteScore
20 DaysMedian Time to First Decision
Q1Highest JCR Category Ranking
Mathematical and Computational Applications
Open Access
1,677 Articles
Launched in 1996
2.1Impact Factor
-CiteScore
25 DaysMedian Time to First Decision
Q2Highest JCR Category Ranking

Published Papers