Quantitative Biosciences

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A01=Joshua S. Weitz
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Author_Joshua S. Weitz
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Bacteria
Category1=Non-Fiction
Category=GPH
Category=PS
Category=PSAX
Category=UYM
Cell
Coli
Concentration
Constant
COP=United States
Current
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Density
Direction
Disease
Distribution
Dynamical
Dynamics
Environment
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Equilibrium
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Event
Evolution
Evolutionary
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Fitness
Force
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Function
Game
Gene
Growth
Infectious
Input
Interactions
Language_English
Levels
Mean
Models
Molecules
Motion
Mrna
Mutants
Mutation
Neurons
Nonlinear
Note
Organisms
Output
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Payoff
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Poisson
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Prey
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Proteins
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Random
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Scale
softlaunch
Steady
Stochastic
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Systems
Total
Transcription
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Variation
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Viruses
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Water

Product details

  • ISBN 9780691181509
  • Dimensions: 203 x 254mm
  • Publication Date: 05 Mar 2024
  • Publisher: Princeton University Press
  • Publication City/Country: US
  • Product Form: Hardback
  • Language: English
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A hands-on approach to quantitative reasoning in the life sciences

Quantitative Biosciences establishes the quantitative principles of how living systems work across scales, drawing on classic and modern discoveries to present a case study approach that links mechanisms, models, and measurements. Each case study is organized around a central question in the life sciences: Are mutations dependent on selection? How do cells respond to fluctuating signals in the environment? How do organisms move in flocks given local sensing? How does the size of an epidemic depend on its initial speed of spread? Each question provides the basis for introducing landmark advances in the life sciences while teaching students—whether from the life sciences, physics, computational sciences, engineering, or mathematics—how to reason quantitatively about living systems given uncertainty.

  • Draws on real-world case studies in molecular and cellular biosciences, organismal behavior and physiology, and populations and ecological communities
  • Stand-alone lab guides available in Python, R, and MATLAB help students move from learning in the classroom to doing research in practice
  • Homework exercises build on the lab guides, emphasizing computational model development and analysis rather than pencil-and-paper derivations
  • Suitable for capstone undergraduate classes, foundational graduate classes, or as part of interdisciplinary courses for students from quantitative backgrounds
  • Can be used as part of conventional, flipped, or hybrid instruction formats
  • Additional materials available to instructors, including lesson plans and homework solutions
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: Dynamics of Viruses and Their Microbial Hosts (Princeton).

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