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Using mathematics to understand biol...
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Segal, Rebecca.
Using mathematics to understand biological complexityfrom cells to populations /
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Using mathematics to understand biological complexityedited by Rebecca Segal, Blerta Shtylla, Suzanne Sindi.
其他題名:
from cells to populations /
其他作者:
Segal, Rebecca.
出版者:
Cham :Springer International Publishing :2021.
面頁冊數:
v, 216 p. :ill. (some col.), digital ;24 cm.
Contained By:
Springer Nature eBook
標題:
Biomathematics.
電子資源:
https://doi.org/10.1007/978-3-030-57129-0
ISBN:
9783030571290$q(electronic bk.)
Using mathematics to understand biological complexityfrom cells to populations /
Using mathematics to understand biological complexity
from cells to populations /[electronic resource] :edited by Rebecca Segal, Blerta Shtylla, Suzanne Sindi. - Cham :Springer International Publishing :2021. - v, 216 p. :ill. (some col.), digital ;24 cm. - Association for women in mathematics series,v.222364-5733 ;. - Association for women in mathematics series ;v.1..
This volume tackles a variety of biological and medical questions using mathematical models to understand complex system dynamics. Working in collaborative teams of six, each with a senior research mentor, researchers developed new mathematical models to address questions in a range of application areas. Topics include retinal degeneration, biopolymer dynamics, the topological structure of DNA, ensemble analysis, multidrug-resistant organisms, tumor growth modeling, and geospatial modeling of malaria. The work is the result of newly formed collaborative groups begun during the Collaborative Workshop for Woman in Mathematical Biology hosted by the Institute of Pure and Applied Mathematics at UCLA in June 2019. Previous workshops in this series have occurred at IMA, NIMBioS, and MBI.
ISBN: 9783030571290$q(electronic bk.)
Standard No.: 10.1007/978-3-030-57129-0doiSubjects--Topical Terms:
212374
Biomathematics.
LC Class. No.: QH323.5
Dewey Class. No.: 570.151
Using mathematics to understand biological complexityfrom cells to populations /
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