CSCI 315
Computational Biology Spring 2020
Division III Quantative/Formal Reasoning
Cross-listed PHYS 315 / CSCI 315

Class Details

This course will provide an overview of Computational Biology, the application of computational, mathematical, statistical, and physical problem-solving techniques to interpret the rapidly expanding amount of biological data. Topics covered will include database searching, DNA sequence alignment, clustering, RNA structure prediction, protein structural alignment, methods of analyzing gene expression, networks, and genome assembly using techniques such as string matching, dynamic programming, hidden Markov models, and expectation-maximization.
The Class: Format: lecture
Limit: 10
Expected: 8
Class#: 3876
Grading: no pass/fail option, no fifth course option
Requirements/Evaluation: weekly Python programming assignments, problem sets, a few quizzes and a final project
Prerequisites: programming experience (e.g., CSCI 136), mathematics (PHYS/MATH 210 or MATH 150), and physical science (PHYS 142 or 151, or CHEM 151 or 153 or 155), or permission of instructor
Enrollment Preferences: based on seniority
Distributions: Division III Quantative/Formal Reasoning
Notes: This course is cross-listed and the prefixes carry the following divisional credit:
PHYS 315 Division III CSCI 315 Division III
Attributes: BIGP Recommended Courses

Class Grid

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