"The book first develops the frameworks needed to understand modern ideas about inference from data, as they relate to biological physics research. Later chapters develop stochastic simulation as a tool to handle more complex systems, and then dynamical systems theory applied to cellular feedback control networks, both natural and synthetic. Along the way, students also see the foundations of revolutionary advances in imaging (superresolution and cryo-electron microscopy), along with epidemic modeling, mechanobiology, excitable media, and more. The text is intended for a one-semester course for science and engineering undergraduates who have taken first-year physics. However, Track-2 sections after each chapter also make it useful for a graduate-level course. Dozens of problems at all levels, many of them new in this edition, help students to gain simulation and data visualization skills useful in any branch of quantitative science research"-- Provided by publisher.