Computational and Systems Biology majors select a coherent integration of courses from one of three designated tracks: bioinformatics, biological data sciences, or dynamical modeling. The synergy for all tracks is integrative systems, information, and computational systems modeling sciences in biology. The focus is primarily quantitative, as mastery of advanced quantitative skills is essential for multidisciplinary understanding. Each track emphasizes different systems or modalities, and modeling or other computational approaches. Students choose one of the three tracks when they declare the major. Well-justified customized tracks may also be approved by the faculty.<br><br>The dynamical modeling track seeks to provide students a strong foundation in the use of mathematical and computational models for analyzing biological systems. The modeling approaches are based on a varied set of approaches such as partial differential equations, stochastic equations, dynamical systems theory, stability theory and linear algebra, network theory, cellular automata, and numerical methods. Dynamical models are the heart of evolution that underpin all of biology and can be applied to disease spread, tumor growth and treatment, wound healing, cell migration, blood flow, ecology, climate change biology, population genetics, evolutionary theory, game theory, and scaling theory. Models are tailored based on the biological and physical details of the system and can often be simplified or used to build intuition based on the associated timescales and spatial dimensionsfrom cellular signaling and transcriptional regulation to communication between organs through hormones to consumer-resource interactions among species. The track allows students to develop quantitative approaches to interpret complex biological systems and is a gateway towards careers in biotechnology and academia.