living matter lab
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[https://link.springer.com/book/10.1007/978-3-030-82890-5 computational epidemiology] <br>
[hallo https://link.springer.com/book/10.1007/978-3-030-82890-5] <br>
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data-driven modeling of COVID-19 <br>
springer nature, 2021  <br>
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springer nature, 2021  <br> <br>
[[preface]], [http://link.springer.com/book/10.1007%2F978-1-4471-6599-6 table of contents] <br>
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if you are a student, educator, basic scientist, or medical researcher in the natural or social sciences, or someone passionate about big data and human health: this book is for you! it is a reflection on the role of data-driven modeling during the
 
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COVID-19 pandemic, motivated by the curiosity to understand it. because science.<br>
contributions by <br>
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saroj nayak, suvranu de, reinhold lipowsky, wonmuk hwang,
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chris jacobs, tarek zohdi, arturas ziemys,
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james weiss, jay humphrey, michael sacks, raul valencia
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Latest revision as of 17:27, 29 September 2021

[edit] new textbook!

COVIDbook.jpg
computational epidemiology
data-driven modeling of COVID-19
springer nature, 2021

if you are a student, educator, basic scientist, or medical researcher in the natural or social sciences, or someone passionate about big data and human health: this book is for you! it is a reflection on the role of data-driven modeling during the COVID-19 pandemic, motivated by the curiosity to understand it. because science.