The scientific field corresponding to Data Driven Modeling in Mathematical Biology is of concern to researchers and/or research teams using mathematical models of dynamical systems type (discrete or continuous, deterministic or stochastic) to interpret experimental data, in the field of biology or of medicine. One of the reference books in the field is the work by J.D. Murray "Mathematical Biology". Works comprising a first statistical-type approach, making it possible to classify and interpret the experimental data, as well as articles aimed at an explanation of the phenomena observed and /or at the proposal of new experiments or new collections of observables already present in public repositories, but not yet used, will be appreciated.
This Research Topic in Data Driven Modeling in Mathematical Biology aim to focus on i) the construction of phenomenological models from the experimental data and ii) the development of explanatory mathematical models, based on the use of dynamic systems (discrete Boolean or random, and continuous differential or stochastic). The interpretation of the data, the classification and the explanation of the observed phenomena within the framework of these models, constitute the important outcomes of the proposed approach.
The articles concerning the inverse method, namely the model driven acquisition approach corresponding to the best choice and the best sampling of the experimental data to allow the fit of the model to the data will also be considered.
Articles on the following topics are welcome:
- Contagious diseases dynamics
- Morphogenesis
- Origin of Life
- Metabolic networks dynamics
- Neural networks dynamics
Theoretical articles coming from the field of theoretical biology and including an explanatory approach based on a new mathematical model or on a new statistical method will also be welcome.
The scientific field corresponding to Data Driven Modeling in Mathematical Biology is of concern to researchers and/or research teams using mathematical models of dynamical systems type (discrete or continuous, deterministic or stochastic) to interpret experimental data, in the field of biology or of medicine. One of the reference books in the field is the work by J.D. Murray "Mathematical Biology". Works comprising a first statistical-type approach, making it possible to classify and interpret the experimental data, as well as articles aimed at an explanation of the phenomena observed and /or at the proposal of new experiments or new collections of observables already present in public repositories, but not yet used, will be appreciated.
This Research Topic in Data Driven Modeling in Mathematical Biology aim to focus on i) the construction of phenomenological models from the experimental data and ii) the development of explanatory mathematical models, based on the use of dynamic systems (discrete Boolean or random, and continuous differential or stochastic). The interpretation of the data, the classification and the explanation of the observed phenomena within the framework of these models, constitute the important outcomes of the proposed approach.
The articles concerning the inverse method, namely the model driven acquisition approach corresponding to the best choice and the best sampling of the experimental data to allow the fit of the model to the data will also be considered.
Articles on the following topics are welcome:
- Contagious diseases dynamics
- Morphogenesis
- Origin of Life
- Metabolic networks dynamics
- Neural networks dynamics
Theoretical articles coming from the field of theoretical biology and including an explanatory approach based on a new mathematical model or on a new statistical method will also be welcome.
