6.096 | Spring 2005 | Undergraduate

Algorithms for Computational Biology

Course Description

This course is offered to undergraduates and addresses several algorithmic challenges in computational biology. The principles of algorithmic design for biological datasets are studied and existing algorithms analyzed for application to real datasets. Topics covered include: biological sequence analysis, gene …
This course is offered to undergraduates and addresses several algorithmic challenges in computational biology. The principles of algorithmic design for biological datasets are studied and existing algorithms analyzed for application to real datasets. Topics covered include: biological sequence analysis, gene identification, regulatory motif discovery, genome assembly, genome duplication and rearrangements, evolutionary theory, clustering algorithms, and scale-free networks.
Learning Resource Types
Lecture Notes
Programming Assignments
Problem Sets
Challenges in Computational Biology
Pictographic representation of the challenges in computational biology. (Figure by MIT OpenCourseWare. Courtesy of Prof. Manolis Kellis.)