CSCI 315
Computational Biology Spring 2023
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 statistics.
The Class: Format: lecture
Limit: 10
Expected: 8
Class#: 4045
Grading: no pass/fail option, no fifth course option
Requirements/Evaluation: weekly Python programming assignments, code reviews, problem sets, plus 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: courage
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
QFR Notes: problem sets and programming assignments
Attributes: BIGP Courses

Class Grid

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