BIOM 315 - Computational Biomedical Engineering:

Introduces techniques for constructing predictive or analytical engineering models for biological processes.  Teaches modeling approaches using example problems in transport, mechanics, bioelectricity, molecular dynamics, tissue assembly, and imaging.  Problem sets will include the implementation and analysis of numerical techniques for (1) integration, differentiation, and root finding (2) systems of linear and nonlinear equations, (3) optimization and linear programming, and (4) ODEs and PDEs.  Advanced examples in tissue morphogenesis, cellular reaction networks, and image processing will be presented.

Offered in the spring semester.  Course syllabus from spring 2008.
 

BIOM 896 - Computational Systems Biology:

This graduate level course introduces techniques for constructing mathematical and computational models of biological processes at many levels of organizational scale-from genome to whole-tissue.  Students will rotate through several modules where they will hear lectures, read literature, and participate in discussions focused on the various modeling techniques.  In each module, students will learn: (1) Which modeling techniques are best suited for addressing biological problems of different scales, (2) Quantitative characterization of biological properties (e.g., robustness), and (3) What constitutes a valid assumption and how can complex problems in biology be simplified while maintaining biological relevance.  Specific modules will teach computational techniques for:  1) genome bioinformatics (e.g., genome-scale protein sequence comparisons), 2) genome network analysis (e.g., metabolic network reconstruction & analysis), 3) multi-cellular simulations (e.g., agent-based modeling of tissue patterning), 4) whole-organ analysis (e.g., finite element analysis of heart function).

Offered in the spring semester.  Course syllabus from spring 2008.