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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Episoder(4)

Postscript: Where to go next

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

1 Feb 20101min

Lecture 21: Uses of multiple sequence alignment

Use of multiple sequence alignment to build a model of a set of biologically related sequences. Profiles, log-odds ratios.

22 Jan 20104min

Lecture 12: Expected longest common substring II

Completion of the analysis of the expected length of the longest common substring in two random strings

12 Jan 20106min

Lecture 7: From alignment graphs to formal dynamic programming

In this class, we move from the visual alignment graph to a purely symbolic treatment of how to compute sequence similarity and optimal alignment using dynamic programming.

7 Jan 20108min