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Using mathematics to understand biological complexity: from cells to populations

This volume tackles a variety of biological and medical questions using mathematical models to understand complex system dynamics. Working in collaborative teams of six, each with a senior research mentor, researchers developed new mathematical models to address questions in a range of application a...

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Detalles Bibliográficos
Autores principales: Segal, Rebecca, Shtylla, Blerta, Sindi, Suzanne
Lenguaje:eng
Publicado: Springer 2021
Materias:
Acceso en línea:https://dx.doi.org/10.1007/978-3-030-57129-0
http://cds.cern.ch/record/2749370
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author Segal, Rebecca
Shtylla, Blerta
Sindi, Suzanne
author_facet Segal, Rebecca
Shtylla, Blerta
Sindi, Suzanne
author_sort Segal, Rebecca
collection CERN
description This volume tackles a variety of biological and medical questions using mathematical models to understand complex system dynamics. Working in collaborative teams of six, each with a senior research mentor, researchers developed new mathematical models to address questions in a range of application areas. Topics include retinal degeneration, biopolymer dynamics, the topological structure of DNA, ensemble analysis, multidrug-resistant organisms, tumor growth modeling, and geospatial modeling of malaria. The work is the result of newly formed collaborative groups begun during the Collaborative Workshop for Woman in Mathematical Biology hosted by the Institute of Pure and Applied Mathematics at UCLA in June 2019. Previous workshops in this series have occurred at IMA, NIMBioS, and MBI.
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institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2021
publisher Springer
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spelling cern-27493702021-04-21T16:44:01Zdoi:10.1007/978-3-030-57129-0http://cds.cern.ch/record/2749370engSegal, RebeccaShtylla, BlertaSindi, SuzanneUsing mathematics to understand biological complexity: from cells to populationsMathematical Physics and MathematicsThis volume tackles a variety of biological and medical questions using mathematical models to understand complex system dynamics. Working in collaborative teams of six, each with a senior research mentor, researchers developed new mathematical models to address questions in a range of application areas. Topics include retinal degeneration, biopolymer dynamics, the topological structure of DNA, ensemble analysis, multidrug-resistant organisms, tumor growth modeling, and geospatial modeling of malaria. The work is the result of newly formed collaborative groups begun during the Collaborative Workshop for Woman in Mathematical Biology hosted by the Institute of Pure and Applied Mathematics at UCLA in June 2019. Previous workshops in this series have occurred at IMA, NIMBioS, and MBI.Springeroai:cds.cern.ch:27493702021
spellingShingle Mathematical Physics and Mathematics
Segal, Rebecca
Shtylla, Blerta
Sindi, Suzanne
Using mathematics to understand biological complexity: from cells to populations
title Using mathematics to understand biological complexity: from cells to populations
title_full Using mathematics to understand biological complexity: from cells to populations
title_fullStr Using mathematics to understand biological complexity: from cells to populations
title_full_unstemmed Using mathematics to understand biological complexity: from cells to populations
title_short Using mathematics to understand biological complexity: from cells to populations
title_sort using mathematics to understand biological complexity: from cells to populations
topic Mathematical Physics and Mathematics
url https://dx.doi.org/10.1007/978-3-030-57129-0
http://cds.cern.ch/record/2749370
work_keys_str_mv AT segalrebecca usingmathematicstounderstandbiologicalcomplexityfromcellstopopulations
AT shtyllablerta usingmathematicstounderstandbiologicalcomplexityfromcellstopopulations
AT sindisuzanne usingmathematicstounderstandbiologicalcomplexityfromcellstopopulations