CS 166-01 Computational Systems Biology

Computational modeling of complex biological systems to analyze their emergent properties and understand or predict system behavior. Molecular and protein modeling in the context of biochemical networks. Application of these models across a select set of applications such as metabolomics, gut microbiome analysis, modularity analysis, flux balance analysis, and biological discovery. Introductions to machine learning, linear systems, and statistical concepts that are commonly used in systems biology.