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Oct 31, 2024
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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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