Fundamental Algorithms in Bioinformatics

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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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Lecture 10: End-gap-free alignment and whole-genome shotgun sequencing Jan 11, 2010

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End-gap-free alignment using dynamic programming. Example from whole-genome shotgun sequencing.

Lecture 9: Local sequence alignment Jan 10, 2010

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In depth treatment of local alignment using dynamic programming.

Lecture 8: Sequence alignment using dynamic programming — continued Jan 08, 2010

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Continuation of the discussion of how to compute similarity and optimal sequence alignment using dynamic programming. Local as well as global alignment.

Lecture 7: From alignment graphs to formal dynamic programming Jan 07, 2010

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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.

Lecture 6: Computing similarity using an alignment graph Jan 06, 2010

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Continuation of the discussion of how to efficiently compute the similarity of two sequences. Introduction to the traceback operation to find the optimal alignment.

Lecture 5: Computing sequence similarity Jan 05, 2010

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Introduction to computational efficiency. Introduction to how we actually compute sequence similarity efficiently.

Lecture 4: Extending the model of sequence similarity Jan 04, 2010

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Review of the definition of sequence similarity and extensions of the model for greater biological fidelity. Introduction to parametric sequence alignment.

Lecture 3: Defining sequence similarity Jan 03, 2010

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Definition of sequence similarity and string alignment, counting alignments the need for fast computation.

Lecture 2: Further introduction Jan 02, 2010

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Continuation of the introduction to the course and to bioinformatics. The biological utility of the similarity of sequences. The first fact of bio-sequence analysis.

Lecture 1: Introduction to bioinformatics and the course Jan 01, 2010

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Introduction to the course and bioinformatics. Why we do bioinformatics, how it relates to genomics and to the changing modalities of biology.

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