At the core of biological complexity are the small machines that maintain the whole: the protein molecules. Proteins are encoded by DNA sequences, spontaneously adopt unique three-dimensional shapes, and perform a wide range of biological functions in living systems. Scientists from a broad range of disciplines are fascinated by these biological machines and use computational means to study the evolution, biophysical properties and biological context of proteins. This book discusses the interface between the different disciplines and the mixed sets of theoretical and computational methods used by each to study proteins. Tools vary from machine learning and statistical methods to text matching and identification of homologous proteins, to statistical physics formulation of random energies and protein folding, and to molecular dynamic simulations of proteins in action. Protein Modeling with Bioinformatics and Biophysics will benefit scientists and advanced-level students interested in this interdisciplinary field.