Mathematical Modeling of Biological Systems
Mathematical modeling is a powerful approach supporting the investigation of open problems in natural sciences, in particular physics, biology and medicine. Applied mathematics allows to translate the available information about real-world phenomena into mathematical objects and concepts. Mathematic...
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| Formato: | Online |
|---|---|
| Idioma: | inglês |
| Publicado em: |
MDPI - Multidisciplinary Digital Publishing Institute
2022
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| Assuntos: | |
| Acesso em linha: | ONIX_20220224_9783036527659_59 |
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| _version_ | 1869518633488613376 |
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| collection | Directory of Open Access Books |
| description | Mathematical modeling is a powerful approach supporting the investigation of open problems in natural sciences, in particular physics, biology and medicine. Applied mathematics allows to translate the available information about real-world phenomena into mathematical objects and concepts. Mathematical models are useful descriptive tools that allow to gather the salient aspects of complex biological systems along with their fundamental governing laws, by elucidating the system behavior in time and space, also evidencing symmetry, or symmetry breaking, in geometry and morphology. Additionally, mathematical models are useful predictive tools able to reliably forecast the future system evolution or its response to specific inputs. More importantly, concerning biomedical systems, such models can even become prescriptive tools, allowing effective, sometimes optimal, intervention strategies for the treatment and control of pathological states to be planned. The application of mathematical physics, nonlinear analysis, systems and control theory to the study of biological and medical systems results in the formulation of new challenging problems for the scientific community. This Special Issue includes innovative contributions of experienced researchers in the field of mathematical modelling applied to biology and medicine. |
| format | Online |
| id | doab-20.500.12854ir-78761 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2022 |
| publishDateRange | 2022 |
| publishDateSort | 2022 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-787612024-03-30T12:51:05Z Mathematical Modeling of Biological Systems Papa, Federico Sinisgalli, Carmela COVID-19 seasonality S.I.R. models mathematical modeling forced seasonality confounding variables uncertainty Atangana–Baleanu Caputo eco-epidemiology Rosenzweig–MacArthur epidemic ODE model COVID-19 spread in Italy system control and identification blood microcirculation ultrafiltration process vasomotion Fårhæus–Lindquist effect type-1 diabetes mellitus global analysis β cells regulatory system dynamical systems network optimization stability analysis global attractor relative entropy information geometry Voronoi diagram diffusion process bivariate probability density function diameter polygon area stand density predictive microbiology lactic acid bacteria batch fermentation primary mathematical model bacterial growth bounded noises kinetic theory active particles statistical mechanics population dynamics Fokker–Planck equation mathematical oncology ecology noise induced transitions systems biology enzymatic reactions quadratization ODE integration thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries Mathematical modeling is a powerful approach supporting the investigation of open problems in natural sciences, in particular physics, biology and medicine. Applied mathematics allows to translate the available information about real-world phenomena into mathematical objects and concepts. Mathematical models are useful descriptive tools that allow to gather the salient aspects of complex biological systems along with their fundamental governing laws, by elucidating the system behavior in time and space, also evidencing symmetry, or symmetry breaking, in geometry and morphology. Additionally, mathematical models are useful predictive tools able to reliably forecast the future system evolution or its response to specific inputs. More importantly, concerning biomedical systems, such models can even become prescriptive tools, allowing effective, sometimes optimal, intervention strategies for the treatment and control of pathological states to be planned. The application of mathematical physics, nonlinear analysis, systems and control theory to the study of biological and medical systems results in the formulation of new challenging problems for the scientific community. This Special Issue includes innovative contributions of experienced researchers in the field of mathematical modelling applied to biology and medicine. 2022-02-24T10:35:36Z 2022-02-24T10:35:36Z 2022 book ONIX_20220224_9783036527659_59 9783036527659 9783036527642 https://directory.doabooks.org/handle/20.500.12854/78761 eng image/jpeg Attribution 4.0 International https://mdpi.com/books/pdfview/book/4853 https://mdpi.com/books/pdfview/book/4853 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-0365-2765-9 10.3390/books978-3-0365-2765-9 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783036527659 9783036527642 218 Basel open access |
| spellingShingle | COVID-19 seasonality S.I.R. models mathematical modeling forced seasonality confounding variables uncertainty Atangana–Baleanu Caputo eco-epidemiology Rosenzweig–MacArthur epidemic ODE model COVID-19 spread in Italy system control and identification blood microcirculation ultrafiltration process vasomotion Fårhæus–Lindquist effect type-1 diabetes mellitus global analysis β cells regulatory system dynamical systems network optimization stability analysis global attractor relative entropy information geometry Voronoi diagram diffusion process bivariate probability density function diameter polygon area stand density predictive microbiology lactic acid bacteria batch fermentation primary mathematical model bacterial growth bounded noises kinetic theory active particles statistical mechanics population dynamics Fokker–Planck equation mathematical oncology ecology noise induced transitions systems biology enzymatic reactions quadratization ODE integration thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries Mathematical Modeling of Biological Systems |
| title | Mathematical Modeling of Biological Systems |
| title_full | Mathematical Modeling of Biological Systems |
| title_fullStr | Mathematical Modeling of Biological Systems |
| title_full_unstemmed | Mathematical Modeling of Biological Systems |
| title_short | Mathematical Modeling of Biological Systems |
| title_sort | mathematical modeling of biological systems |
| topic | COVID-19 seasonality S.I.R. models mathematical modeling forced seasonality confounding variables uncertainty Atangana–Baleanu Caputo eco-epidemiology Rosenzweig–MacArthur epidemic ODE model COVID-19 spread in Italy system control and identification blood microcirculation ultrafiltration process vasomotion Fårhæus–Lindquist effect type-1 diabetes mellitus global analysis β cells regulatory system dynamical systems network optimization stability analysis global attractor relative entropy information geometry Voronoi diagram diffusion process bivariate probability density function diameter polygon area stand density predictive microbiology lactic acid bacteria batch fermentation primary mathematical model bacterial growth bounded noises kinetic theory active particles statistical mechanics population dynamics Fokker–Planck equation mathematical oncology ecology noise induced transitions systems biology enzymatic reactions quadratization ODE integration thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries |
| topic_facet | COVID-19 seasonality S.I.R. models mathematical modeling forced seasonality confounding variables uncertainty Atangana–Baleanu Caputo eco-epidemiology Rosenzweig–MacArthur epidemic ODE model COVID-19 spread in Italy system control and identification blood microcirculation ultrafiltration process vasomotion Fårhæus–Lindquist effect type-1 diabetes mellitus global analysis β cells regulatory system dynamical systems network optimization stability analysis global attractor relative entropy information geometry Voronoi diagram diffusion process bivariate probability density function diameter polygon area stand density predictive microbiology lactic acid bacteria batch fermentation primary mathematical model bacterial growth bounded noises kinetic theory active particles statistical mechanics population dynamics Fokker–Planck equation mathematical oncology ecology noise induced transitions systems biology enzymatic reactions quadratization ODE integration thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries |
| url | ONIX_20220224_9783036527659_59 |