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.
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: F9:30-11 Units: 2-0-4 (U) Prereq: 6.001, 7.01 Webpage: http://web.mit.edu/manoli/6.096/ Contact: firstname.lastname@example.org
Lectures and homeworks are coordinated with 6.046 (MW9:30-11), the quintessential introductory algorithms course taught by Charles Leiserson and Ron Rivest.