6.096 Algorithms for Computational Biology

As taught in: Spring 2005

Challenges in Computational Biology

Pictographic representation of the challenges in computational biology. (Figure by MIT OpenCourseWare. Courtesy of Prof. Manolis Kellis.)




Prof. Manolis Kellis

Course Features

Course Highlights

This course features a complete set of homework assignments.

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 identification, regulatory motif discovery, genome assembly, genome duplication and rearrangements, evolutionary theory, clustering algorithms, and scale-free networks.

Technical Requirements

Special software is required to use some of the files in this course: .py.