This graduate course is an introduction to the computational tools most commonly applied in biological and physiological research, with emphasis on the art of using models, programming and simulation to reach useful conclusions and insights. The first half of the course is an introduction to the Unix operating system, the elements of programming, and basic methods of numerical analysis. Specific topics include exact and iterative methods for the solution of large systems, differentiation and interpolation numerical integration, Monte Carlo methods and statistical bootstrap methods, Fourier transform and spectral methods, and also finite element and finite difference methods for the solution of ordinary and partial differential equations. Each weekly lecture is accompanied by a computer lab in which the students will gain experience in the use of the techniques under study. The last half of the course uses a case study approach comprised of several two-week modules designed to immerse students in a variety of specific bioengineeering applications covering the range from genes and molecules to cells organs and systems. Each module will begin with lectures on the derivation and implementation of a particular model or computational algorithm and be accompanied by a related computational mini-project.