Quantitative Biosciences Companion in Python (Paperback)

Joshua S. Weitz

ISBN 10: 0691255679 / ISBN 13: 9780691255675

Editore: Princeton University Press, New Jersey, 2024

Riguardo questo articolo

Paperback. 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. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Codice articolo 9780691255675

Dati bibliografici

• Titolo: Quantitative Biosciences Companion in Python (Paperback)
• Editore: Princeton University Press, New Jersey
• Data di pubblicazione: 2024
• Lingua: Inglese
• ISBN 10: 0691255679
• ISBN 13: 9780691255675
• Rilegatura: Paperback
• Condizione: new

Descrizione articolo

Riassunto

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

Informazioni sull?autore

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.