Quantitative Biosciences Companion in Python: Dynamics across Cells, Organisms, and Populations

Quantitative Biosciences Companion in Python: Dynamics across Cells, Organisms, and Populations
Author: Joshua S. Weitz (Author), Nolan English (Author), Alexander B. Lee (Author), Ali Zamani (Author)
Publisher finelybook 出版社:‏ Princeton University Press
Publication Date 出版日期:‏ 2024-03-05
Language 语言: English
Print Length 页数: 272 pages
ISBN-10: 0691255679
ISBN-13: 9780691255675

Book Description

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 organized 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.

• Draws on real-world case studies in molecular and cellular biosciences, organismal behavior and physiology, and populations and ecological communities
• Encourages good coding practices, clear and understandable modeling, and accessible presentation of results
• Helps students to develop a diverse repertoire of simulation approaches, enabling them to model at the appropriate scale
• Builds practical expertise in a range of methods, including sampling from probability distributions, stochastic branching processes, continuous time modeling, Markov chains, bifurcation analysis, partial differential equations, and agent-based simulations
• Bridges the gap between the classroom and research discovery, helping students to think independently, troubleshoot and resolve problems, and embark on research of their own
• Stand-alone computational lab guides for Quantitative Biosciences also available in R and MATLAB