Trends in Modeling and Simulation of Biological Systems
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Computational and Applied Mathematics".
Deadline for manuscript submissions: closed (28 February 2021) | Viewed by 3079
Special Issue Editor
Interests: cellular computing and information processing; molecular automata modeling; evolutionary algorithms and computation; towards a morphogenetic field theory; quantum computing applied to biology; evolutionary synthetic biology; sentiment simulation models in AI and empathic chatbots; numerical models and machine learning methods in natural science
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Special Issue Information
Dear Colleagues,
The modeling and simulation of biological systems is mostly based on traditional techniques, such as the use of differential equations and linear algebra, among others. Applying such mathematical approaches, it has become possible to describe in mathematical language biological phenomena such as morphogenesis, evolution, self-organization, learning, etc. Moreover, with these techniques, it is also possible to depict a biological phenomenon at the different levels of observation (molecular, cellular, individual, population, ecosystem, etc.). Nevertheless, for years now, alternative methods of modeling and simulation have been applied, obtaining interesting results that complement those obtained by traditional methods. For example, diseases such as cancer or the coexistence of predators and preys according to the Volterra–Lotka model can be modeled with differential equations or alternatively using the cellular automata technique. In the same way, the modeling and simulation of Darwinian evolution can be conducted with differential equations or alternatively by means of heuristic methods, for example, genetic algorithms.
The goal of this Special Issue is to publish articles in which a biological system is modeled and simulated by applying alternative techniques to traditional methods or using a combination, for example, of differential equations with such alternative methods. Alternative methods may include but are not limited to cellular automata, heuristic procedures, etc. or less-standard mathematical procedures in biology, e.g., group theory, or approaches from domains such as topology.
Prof. Dr. R. Lahoz-Beltra
Guest Editor
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Keywords
- Differential equations
- Linear algebra
- Modeling biological systems
- Simulation methods
- Heuristic approaches
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