BIOL 331 - Computational Systems Biology

A survey of network models used to gain a systems-level understanding of biological processes. Topics include computational models of gene regulation, signal transduction pathways, protein-protein interactions, and metabolic pathways. Laboratory exercises will involve building a collection of biological networks from public data, implementing a graph library and foundational algorithms, and interpreting computational results. A programming-based independent project will answer biological questions by applying graph algorithms to experimental data.

Unit(s): 1
Group Distribution Requirement(s): Distribution Group III, Distribution Group III-Data Collection and Analysis
Prerequisite(s): BIOL 101 and BIOL 102, and either BIOL 131 or CSCI 121
Instructional Method: Lecture-laboratory
Grading Mode: Letter grading (A-F)
Group Distribution Learning Outcome(s):

Use and evaluate quantitative data or modeling, or use logical/mathematical reasoning to evaluate, test or prove statements.
Given a problem or question, formulate a hypothesis or conjecture, and design an experiment, collect data, or use mathematical reasoning to test or validate it.
Collect, interpret, and analyze data.

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