CS 4775

CS 4775

Course information provided by the Courses of Study 2019-2020.

Computational methods for analyzing genetic and genomic data.  Topics include sequence alignment, hidden Markov Models for discovering sequence features, motif finding using Gibbs sampling, phylogenetic tree reconstruction, inferring haplotypes, and local and global ancestry inference. Prior knowledge of biology is not necessary to complete this course.

When Offered Fall.

Prerequisites/Corequisites Prerequisite: BTRY 3010 and at least one course in algorithms.

Distribution Category (PBSS-AS)

Outcomes
  • Understand computational algorithms used for the analysis of genetic and genomic data
  • Formulate computational approaches for solving problems in computational genomics
  • Understand challenges and limitations in inference methods used in computational genetics and genomics

View Enrollment Information

Syllabi: none
  •   Regular Academic Session.  Choose one lecture and one discussion. Combined with: BTRY 4840BTRY 6840

  • 4 Credits Stdnt Opt

  • 12129 CS 4775   LEC 001

  • Prerequisites: BTRY 3010 and CS 2110 or equivalents.

  • 12130 CS 4775   DIS 201