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Fundamental Algorithms in Bioinformatics
By Dan Gusfield
Fundamental Algorithms in Bioinformatics episodes
- Lecture 21: Uses of multiple sequence alignmentUse of multiple sequence alignment to build a model of a set of biologically related sequences. Profiles, log-odds ratios.5 min
- Lecture 20: Multiple sequence alignment IIIThe center tree method and analysis; progressive alignment, guide trees, CLUSTAL, uses of multiple alignment5 min
- Lecture 19: Multiple sequence alignment IIContinuation of multiple sequence alignment; sum-of-pairs objective function; tree consistency theorem; factor-of-two approximation.5 min
- Lecture 18: Multiple sequence alignment IStart of discussion on Multiple Sequence Alignment. sum-of-pairs objective function. Dynamic program solution for three sequences. Program MSA5 min
- Lecture 17: Probability and database searchFurther discussion of probability and database search. Granin and BRCA1 story. Database search used as a filter, not an oracle.4 min
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- Lecture 13: Probability of a complete query match in a databaseContinuation of the topic of probability of matching.Here we look at the probability that a query stringmatches completely, at least once, in a much largerdatabase of strings.4 min
- Lecture 12: Expected longest common substring IICompletion of the analysis of the expected length of the longest common substring in two random strings7 min
About Fundamental Algorithms in Bioinformatics
From the publisher's feed
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.