CS 262
Computational Genomics
Winter 2004
Handout #2: Tentative Course Syllabus

Approximate Syllabus
  • Introduction
    DNA, RNA, proteins, the central dogma in molecular biology, splicing, gene structure

  • Sequence Alignments
    Homology, alignments and dynamic programming
    Local alignment, heuristic local alignment and BLAST
    Advanced alignment techniques: linear space, affine gaps, banded linear time alignments, time warping

  • Hidden Markov Models
    Markov chains and hidden Markov models
    The Viterbi algorithm
    Parameter estimation for HMMs
    Connection between pair HMMs and alignments

  • Applications of alignments and HMMs: Analysis of a genome
    The human genome: chromosomes, repeats, genes, and SNPs
    Gene Recognition
    Suffix Trees
    Comparative genomics, efficient alignment algorithms
    Cross-species comparison-based gene recognition

  • Multiple sequence alignments
    Definition, multidimensional dynamic programming
    Progressive alignment, CLUSTALW
    Expectation maximization, Gibbs sampling
    Applications: microarrays and gene regulation

  • Sequencing of a Genome
    Sequencing methods
    Computational assembly of a genome

  • Conclusion
    Current active areas and open problems in computational genomics
  • Assignment Schedule

    Problem Set Schedule:

    Comments to CS262 Staff