Research Topic

Dynamical Analysis of Biological Systems Possessing Random Noises and its Applications

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About this Research Topic

Mathematical biology is a fast-growing, well-recognized, albeit not clearly defined, subject and is the most exciting modern application of mathematics. The increasing use of mathematics in biology is inevitable as biology becomes more quantitative. Theory of system analysis allows classifying biological systems as reflective ones as far as they react on the changes of existence conditions, explicitly on environment actions and own states. In order to keep the completeness of the system under environmental variability and internal transformations, a biological system is considered to be in dynamic equilibrium, which guarantees the existence of the entire system.

Unlike a deterministic system, a stochastic system is one that is unpredictable because of a random variable. So, it is often used to describe subjects that contain some elements of random or stochastic behavior. Indeed, the analysis and synthesis of the dynamical systems such as stability, bifurcation, chaos and synchronization associated with biological systems subject to disturbances, time delays, uncertainties, and random noise have been the area of significant research interest due to the fact that mathematical or theoretical biology is unquestionably an interdisciplinary science par excellence.

The main aim of this Research Topic is to present recent developments on the dynamical analysis and its application into complex stochastic systems including Hybrid systems, Markovian jump systems, switched systems, 1-D or 2-D chaotic systems and so on. All submissions are expected to contain original ideas and novel approaches. The Research Topic enables researchers worldwide to report their most recent developments and ideas in the field, with a special emphasis on the theoretical or practical technical advances proposed within recent years.

Potential topics include, but are not limited to:

• Modeling and identification methods in biological stochastic systems
• Stability analysis for biological stochastic system
• Chaotic analysis of the generalized Lotka-Volterra 3-species biological stochastic system
• Consequences of delays, uncertainties occurring in biological stochastic systems
• Adaptive biological control for biological stochastic systems
• Adaptive synchronization for biological stochastic systems
• Hybrid / Markov jumping systems / Switched systems in biological networks
• Adaptive synchronization for biological stochastic systems
• Intelligence algorithms for biological stochastic systems


Keywords: Stability, complex stochastic systems, stochastic delayed systems, hybrid /Markov jumping systems, biological stochastic systems


Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

Mathematical biology is a fast-growing, well-recognized, albeit not clearly defined, subject and is the most exciting modern application of mathematics. The increasing use of mathematics in biology is inevitable as biology becomes more quantitative. Theory of system analysis allows classifying biological systems as reflective ones as far as they react on the changes of existence conditions, explicitly on environment actions and own states. In order to keep the completeness of the system under environmental variability and internal transformations, a biological system is considered to be in dynamic equilibrium, which guarantees the existence of the entire system.

Unlike a deterministic system, a stochastic system is one that is unpredictable because of a random variable. So, it is often used to describe subjects that contain some elements of random or stochastic behavior. Indeed, the analysis and synthesis of the dynamical systems such as stability, bifurcation, chaos and synchronization associated with biological systems subject to disturbances, time delays, uncertainties, and random noise have been the area of significant research interest due to the fact that mathematical or theoretical biology is unquestionably an interdisciplinary science par excellence.

The main aim of this Research Topic is to present recent developments on the dynamical analysis and its application into complex stochastic systems including Hybrid systems, Markovian jump systems, switched systems, 1-D or 2-D chaotic systems and so on. All submissions are expected to contain original ideas and novel approaches. The Research Topic enables researchers worldwide to report their most recent developments and ideas in the field, with a special emphasis on the theoretical or practical technical advances proposed within recent years.

Potential topics include, but are not limited to:

• Modeling and identification methods in biological stochastic systems
• Stability analysis for biological stochastic system
• Chaotic analysis of the generalized Lotka-Volterra 3-species biological stochastic system
• Consequences of delays, uncertainties occurring in biological stochastic systems
• Adaptive biological control for biological stochastic systems
• Adaptive synchronization for biological stochastic systems
• Hybrid / Markov jumping systems / Switched systems in biological networks
• Adaptive synchronization for biological stochastic systems
• Intelligence algorithms for biological stochastic systems


Keywords: Stability, complex stochastic systems, stochastic delayed systems, hybrid /Markov jumping systems, biological stochastic systems


Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

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