ECS 124: Fundamental Algorithms in Bioinformatics

ECS 124: Fundamental Algorithms in Bioinformatics (UC Davis). Instructor: Professor Dan Gusfield. This course covers fundamental algorithms for efficient analysis of biological sequences and for building evolutionary trees. This is an undergraduate course taught by UC Davis computer science professor Dan Gusfield 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.

The videos were mostly made in 2002 and edited and somewhat extended in 2014. Despite their age, and despite the fact that "software, databases, websites, and data" in bioinformatics change rapidly, the topics included are still of current importance.


Lecture 01 - Introduction to Bioinformatics and the Course
Lecture 02 - Further Introduction
Lecture 03 - Defining Sequence Similarity
Lecture 04 - Extending the Model of Sequence Similarity
Lecture 05 - Computing Sequence Similarity
Lecture 06 - Computing Similarity Using Alignment Graph
Lecture 07 - From Alignment Graphs to Formal Dynamic Programming
Lecture 08 - Sequence Alignment Using Dynamic Programming (cont.)
Lecture 09 - Local Sequence Alignment
Lecture 10 - End-gap Free Alignment and Whole-genome Shotgun Sequencing
Lecture 11a - Expected Length of the Longest Common Subsequence
Lecture 11b - Expected Length of the Longest Common Substring
Lecture 12 - Expected Longest Common Substring II
Lecture 13 - Probability of a Complete Query Match in a Database
Lecture 14 - BLAST (Basic Local Alignment Search Tool) I
Lecture 15 - BLAST II
Lecture 16 - BLAST Statistics
Lecture 17 - Probability and Database Search
Lecture 18 - Multiple Sequence Alignment I
Lecture 19 - Multiple Sequence Alignment II
Lecture 20 - Multiple Sequence Alignment III
Lecture 21 - Uses of Multiple Sequence Alignment
Lecture 22 - From Profiles to Markov Models
Lecture 23 - Hidden Markov Models
Lecture 24 - Hidden Markov Models and the Viterbi Algorithm
Lecture 25 - From the Viterbi Algorithm to the Forward Algorithm
Lecture 26 - Hidden Markov Models - The Backwards Algorithm
Lecture 27 - Introduction to Evolutionary Trees - Ultrametric Trees
Lecture 28 - Algorithms for Ultrametric Trees - Molecular Clocks
Lecture 29 - Additive Trees and the Neighbor-Joining Algorithm
Lecture 30 - Maximum Parsimony and Minimum Mutation Methods