Editorial Special Issues

Mathematical and computational modeling of biological systems: advances and perspectives

  • Received: 26 September 2021 Accepted: 26 September 2021 Published: 30 September 2021
  • The recent developments in the fields of mathematics and computer sciences have allowed a more accurate description of the dynamics of some biological systems. On the one hand new mathematical frameworks have been proposed and employed in order to gain a complete description of a biological system thus requiring the definition of complicated mathematical structures; on the other hand computational models have been proposed in order to give both a numerical solution of a mathematical model and to derive computation models based on cellular automata and agents. Experimental methods are developed and employed for a quantitative validation of the modeling approaches. This editorial article introduces the topic of this special issue which is devoted to the recent advances and future perspectives of the mathematical and computational frameworks proposed in biosciences.

    Citation: Carlo Bianca. Mathematical and computational modeling of biological systems: advances and perspectives[J]. AIMS Biophysics, 2021, 8(4): 318-321. doi: 10.3934/biophy.2021025

    Related Papers:

  • The recent developments in the fields of mathematics and computer sciences have allowed a more accurate description of the dynamics of some biological systems. On the one hand new mathematical frameworks have been proposed and employed in order to gain a complete description of a biological system thus requiring the definition of complicated mathematical structures; on the other hand computational models have been proposed in order to give both a numerical solution of a mathematical model and to derive computation models based on cellular automata and agents. Experimental methods are developed and employed for a quantitative validation of the modeling approaches. This editorial article introduces the topic of this special issue which is devoted to the recent advances and future perspectives of the mathematical and computational frameworks proposed in biosciences.



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    [1] Bianca C, Bellomo N (2011) Towards a mathematical theory of complex biological systems. Series in Mathematical Biology and Medicine World Scientific Publishing Co. Pte. Ltd. doi: 10.1142/8085
    [2] Nicolis G, Nicolis C (2007) Foundations of complex systems: Nonlinear dynamics. Statistical Physics, Information and Prediction World Scientific Publishing Co. Pte. Ltd.
    [3] Gosak M, Markovič R, Dolenšek J, et al. (2018) Network science of biological systems at different scales: A review. Phys Life Rev 24: 118-135. doi: 10.1016/j.plrev.2017.11.003
    [4] Deuflhard P, Röblitz S (2015) ODE models for systems biological networks. A Guide to Numerical Modelling in Systems Biology Cham: Springer, 1-32.
    [5] Chauvière A, Preziosi L, Verdier C (2010)  Cell mechanics: from single scale-based models to multiscale modeling London: Chapman and Hall/CRC. doi: 10.1201/9781420094558
    [6] Ben Amar M, Bianca C (2016) Towards a unified approach in the modeling of fibrosis: A review with research perspectives. Phys Life Re 17: 61-85. doi: 10.1016/j.plrev.2016.03.005
    [7] Bai Q, Ren F, Fujita K, et al. (2017)  Multi-agent and Complex Systems Singapore: Springer. doi: 10.1007/978-981-10-2564-8
    [8] Heard D, Dent G, Schifeling T, et al. (2015) Agent-based models and microsimulation. Annu Rev Stat Its Appl 2: 259-272. doi: 10.1146/annurev-statistics-010814-020218
    [9] Städter P, Schälte Y, Schmiester L, et al. (2021) Benchmarking of numerical integration methods for ODE models of biological systems. Sci Rep 11: 2696. doi: 10.1038/s41598-021-82196-2
    [10] Sabat L, Kundu CK (2021) History of finite element method: a review. Recent Developments in Sustainable Infrastructure 75: 395-404. doi: 10.1007/978-981-15-4577-1_32
    [11] Rai N, Mondal S (2021) Spectral methods to solve nonlinear problems: A review. Part Differ Equ Appl Math 4: 100043.
    [12] Van Liedekerke P, Palm MM, Jagiella N, et al. (2015) Simulating tissue mechanics with agent-based models: concepts, perspectives and some novel results. Comput Part Mech 2: 401-444. doi: 10.1007/s40571-015-0082-3
    [13] Perea A, Predtetchinski A (2019) An epistemic approach to stochastic games. Int J Game Theory 48: 181-203. doi: 10.1007/s00182-018-0644-8
    [14] Hasdemir D, Hoefsloot HCJ, Smilde AK (2015) Validation and selection of ODE based systems biology models: how to arrive at more reliable decisions. BMC Syst Biol 9: 32. doi: 10.1186/s12918-015-0180-0
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