Fundamental Algorithms in Bioinformatics

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Lecture 19: Multiple sequence alignment II Jan 20, 2010

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Continuation of multiple sequence alignment; sum-of-pairs objective function; tree consistency theorem; factor-of-two approximation.

Lecture 18: Multiple sequence alignment I Jan 19, 2010

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Start of discussion on Multiple Sequence Alignment. sum-of-pairs objective function. Dynamic program solution for three sequences. Program MSA

Lecture 17: Probability and database search Jan 18, 2010

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Further discussion of probability and database search. Granin and BRCA1 story. Database search used as a filter, not an oracle.

Lecture 16: BLAST statistics Jan 17, 2010

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E-values, extreme value distribution, probability of a match

Lecture 15: BLAST II Jan 15, 2010

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Discussion of hashing kmers, E-values, statistics, BLAST II

Lecture 14: BLAST I Jan 14, 2010

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Introduction to the ideas behind BLAST I.

Lecture 13: Probability of a complete query match in a database Jan 13, 2010

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Continuation of the topic of probability of matching. Here we look at the probability that a query string matches completely, at least once, in a much larger database of strings.

Lecture 12: Expected longest common substring II Jan 12, 2010

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

Lecture 11a: Expected Length of the Longest Common Subsequence Jan 11, 2010

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We discuss the expected length of the longest common subsequence between two random strings of lengths n each, and show that it grows linearly with n. This lecture originally contained a discussion both of the expected length of the longest common subsequence and the expected length of the longest common substring. But the video has been split to overcome some technical problems that showed up in the original video.

Lecture 11b: Expected Length of the Longest Common Substring Jan 11, 2010

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We discuss the expected length of the longest common substring (not subsequence) between two random strings of length n each, and show that it grows only logarithmically as a function of n - much slower than the growth of the expected longest common subsequence discussed in Lecture 11a.

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