Quantitative Biosciences: A Hands-on Lab Guide in Python

By Joshua S. Weitz, Nolan English, Alexander B. Lee, Ali Zamani

A comprehensive lab guide in the Python programming language, designed to empower students in the life sciences to think quantitatively about living systems across various scales. This guide is a companion to the textbook Quantitative Biosciences, providing students with the necessary skills to translate biological principles and mathematical concepts into computational models of living systems.

Case Study Approach

This hands-on guide adopts a case study approach, organized around central questions in the life sciences. It introduces 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.

Real-World Applications

The guide draws on real-world case studies in molecular and cellular biosciences, organismal behavior and physiology, and populations and ecological communities. This helps students understand how to apply computational models to real-life scenarios, making the learning experience more engaging and relevant.

Good Coding Practices

The guide emphasizes good coding practices, clear and understandable modeling, and accessible presentation of results. By following these principles, students can develop well-structured and efficient code that effectively communicates their findings.

Diverse Simulation Approaches

Students will learn a diverse repertoire of simulation approaches, enabling them to model at the appropriate scale. This includes sampling from probability distributions, stochastic branching processes, continuous time modeling, Markov chains, bifurcation analysis, partial differential equations, and agent-based simulations.

Practical Expertise

By working through the lab guide, students will develop practical expertise in a range of methods. This will equip them with the skills needed to tackle complex problems in the life sciences and to contribute meaningfully to research projects.

Classroom to Research

The guide 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. By providing a structured learning environment, the guide prepares students for the challenges and opportunities of real-world research.

Stand-Alone Computational Lab Guides

For students who prefer to work in R or MATLAB, stand-alone computational lab guides for Quantitative Biosciences are also available. These guides offer the same comprehensive learning experience, tailored to the specific needs and capabilities of each programming language.

Product Details

Publisher: Princeton University Press (March 5, 2024)

Language: English

Pages: 272

ISBN-10: 0691255679

ISBN-13: 978-0691255675