Tools developed by statistical physicists are of increasing importance in the analysis of complex biological systems. Physics in Molecular Biology, first published in 2005, discusses how physics can be used in modeling life. It begins by summarizing important biological concepts, emphasizing how they differ from the systems normally studied in physics. A variety of topics, ranging from the properties of single molecules to the dynamics of macro-evolution, are studied in terms of simple mathematical models. The main focus of the book is on genes and proteins and how they build systems that compute and respond. The discussion develops from simple to complex systems, and from small-scale to large-scale phenomena. This book will inspire advanced undergraduates and graduate students in physics to approach biological subjects from a physicist's point of view. It is self-contained, requiring no background knowledge of biology, and only familiarity with basic concepts from physics, such as forces, energy, and entropy.

Molecular Machines presents a dynamic new approach to the physics of enzymes and DNA from the perspective of materials science. Unified around the concept of molecular deformability-how proteins and DNA stretch, fold, and change shape-this book describes the complex molecules of life from the innovative perspective of materials properties and dynamics, in contrast to structural or purely chemical approaches. It covers a wealth of topics, including nonlinear deformability of enzymes and DNA; the chemo-dynamic cycle of enzymes; supra-molecular constructions with internal stress; nano-rheology and viscoelasticity; and chemical kinetics, Brownian motion, and barrier crossing. Essential reading for researchers in materials science, engineering, and nanotechnology, the book also describes the landmark experiments that have established the materials properties and energy landscape of large biological molecules. Molecular Machines is also ideal for the classroom. It gives graduate students a working knowledge of model building in statistical mechanics, making it an essential resource for tomorrow's experimentalists in this cutting-edge field. In addition, mathematical methods are introduced in the bio-molecular context-for example, DNA conformational transitions are used to illustrate the transfer matrix formalism. The result is a generalized approach to mathematical problem solving that enables students to apply their findings more broadly. Molecular Machines represents the next leap forward in nanoscience, as researchers strive to harness proteins, enzymes, and DNA as veritable machines in medicine, technology, and beyond.