Fundamental Algorithms in Bioinformatics Podcast - Listen,

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Fundamental Algorithms in Bioinformatics

This course covers fundamental algorithms for efficient analysis of biological sequences and for building evolutionary trees. This is an undergraduate course focusing on the ideas and concepts behind the most central algorithms in biological sequence analysis. Dynamic Programming, Alignment, Hidden Markov Models, Statistical Analysis are emphasized.

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Postscript: Where to go next

Some suggestions of where the student can get more exposure to algorithms for bioinformatics and computational biology.

Published 02/01/10

Lecture 30: Maximum Parsimony and minimum mutation methods

Building evolutionary trees from sequence data. The Maximum Parsimony criteria, the special case of Perfect Phylogeny, and the Fitch-Hartigon dynamic program to minimize mutations when the tree and a sequence alignment are known.

Published 01/31/10

Lecture 29; Additive trees and the Neighbor-Joining algorithm

Additive trees and their construction. The Neighbor-Joining algorithm and its use with near-additive data. Bootstrap values and their misuse.

Published 01/30/10

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