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RBIF 109

Biological Sequence Analysis

This course provides a foundation in sequence analysis and associated algorithms. Topics include homology searching, multiple sequence alignment, transcription factor binding site discovery, phylogenetics, gene prediction, RNAi sequence analysis, Gibbs sampling, Markov chains, Hidden Markov models, Genetic algorithms, information theory, expectation maximization, maximum likelihood, Bayesian methods, Markov chain Monte Carlo methods.


At the end of the course, students will be able to:

Search for homologous sequences.

Build multiple sequence alignments.

Reconstruct phylogenetic trees.

Discover transcription factor binding sites.

Predict genes.

Predict RNAi targets.

Evaluate and compare sequence analysis methods.

Develop their own sequence analysis methods.

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