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A hands-on lab guide in the Python programming language that enables students in the life sciences to reason quantitatively about living systems across scales.
This lab guide accompanies the textbook Quantitative Biosciences, providing students with the skills they need to translate biological principles and mathematical concepts into computational models of living systems. This hands-on guide uses a case study approach organised around central questions in the life sciences, introducing landmark advances in the field while teaching students – whether from the life sciences, physics, computational sciences, engineering, or mathematics – how to reason quantitatively in the face of uncertainty.
Author Biography
Joshua S. Weitz is professor and the Clark Leadership Chair in Data Analytics in the Department of Biology at the University of Maryland. Previously, he held the Tom and Marie Patton Chair in Biological Sciences at the Georgia Institute of Technology, where he founded the Interdisciplinary Graduate Program in Quantitative Biosciences. He is the author of Quantitative Viral Ecology (Princeton).
Nolan English is a postdoctoral researcher at Oak Ridge National Laboratory.
Alexander B. Lee is a data scientist with expertise in developing biological models in Python and MATLAB.
Ali Zamani is associate data developer at Priceline.
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