6.096 - Algorithms for Computational Biology (Spring 2005) Prof. Manolis Kellis This new course covers the algorithmic foundations of computational biology, combining theory with practice. We study the principles of algorithm design for biological datasets, analyze influential algorithms, and apply these to real datasets. Topics include: Strings: biological sequence analysis, gene finding, motif discovery, RNA folding, global and local sequence alignment Genomes: genome assembly, comparative genomics, genome duplication, genome rearrangements, evolutionary theory Networks: gene expression, clustering algorithms, scale-free networks, machine learning applications to genomics (see poster pdf) Class homepage: 6.096 - Algorithms for Computational Biology

Valence visualization of the BLAST algorithm at work

Lectures:

L1: Biological datasets
L2: Regulatory motif discovery
L3: Sequence alignment
L4: RNA folding
L5: Gene finding
L6: Rapid database search
L7: Genome rearrangements
L8: Genome assembly
L9: Evolutionary theory
L10: Gene expression clustering
L11: Gene Network and inference
L13: Scale-free networks
L14: Comparative genomics

Lectures: F9:30-11
Units:  2-0-4 (U)
Prereq: 6.001, 7.01
Webpage: http://web.mit.edu.ezproxyberklee.flo.org/manoli/6.096/
Contact: manoli@mit.edu

Lectures and homeworks are coordinated with 6.046 (MW9:30-11), the quintessential introductory algorithms course taught by Charles Leiserson and Ron Rivest.

How to enroll:

With 6.046:

The best of both worlds! Enroll simultaneously in 6.046 and 6.096. 6.046 meets on MW 930-11. Grading is separate in the two courses.

After 6.046:

If you're already taken algorithms, you can enroll for 6.096 only, as a separate course, with permission of instructors.

Manolis Kellis