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Week 1:
    Lecture 1: Meiosis    (ps  ppt  pdf )
    Lecture 2: A quick overview of human genetic linkage analysis    (ps  ppt  pdf)

Week 2:
    Lecture 1: A quick survey of human 2-point linkage analysis    (ps  ppt  pdf)
    Lecture 2: Biological sequence analysis    (ps  ppt  pdf)

Week 3:
    Lectures 1, 2: Gene expression    (ppt  pdf)

Week 4:
    Lecture 1: Environmental and heritable factors in the causation of cancer    (lectures.pdf  lectures.ppt  lichtenstein.pdf)
    Lecture 2: The genetic epidemiology of cancer (given by Ingileif Hallgrimsdottir)     (risch.pdf)

Week 5:
    Lecture 1: Pairwise sequence comparison    (lecture.pdf  lecture.ppt)
    Lecture 2: Multiple sequence alignment and phylogenetic trees    (lecture.pdf  lecture.ppt)

Week 6:
    Lecture 1: Molecular evolution (given by Von Bing Yap)    (lecture.pdf  lecture.ppt)
    Lecture 2: In silico mapping of complex disease-related traits in mice    (lecture.pdf  mainpaper.pdf  secondarypaper.pdf  lecture.ppt)

Week 7:
    Lecture 1: Completion of lectures 1 and 2 from Week 6.   
    Lecture 2: Preprocessing of cDNA microarray data    (lecture.pdf  lecture.ppt)

Week 8:
    Lecture 1: Estimating expression differences in cDNA microarray experiments    (lecture.pdf  lecture.ppt)
    Lecture 2: Multiple testing in large scale gene expression experiments (given by Yongchao Ge)    (lecture.pdf  lecture.ppt)

Week 9:
    Lecture 1: Introduction to the design of cDNA microarray experiments (given by Jean Yang)    (lecture.pdf  lecture.ppt)
    Lecture 2: From hidden Markov models to stochastic context-free grammars (given by Xiaoyue Zhao)    (lecture.pdf)

Week 10: Spring Break

Week 11:
    Lecture 1: More on multiple testing and the design of cDNA microarray experiments (no new notes)
    Lecture 2: Detecting subtle sequence signals: an intro to the work of J. Liu, C.E. Lawrence, et al. (given by Ingileif Hallgrimsdottir)     (lecture.pdf)

Week 12:
    Lecture 1: Three examples of the EM algorithm     (lecture.pdf  lecture.ppt)
    Lecture 2: The MEME algorithm for motif discovery     (lecture.pdf  lecture.ppt)

Week 13:
    Lecture 1: More on the Gibbs Motif Sampler     (lecture.pdf  lecture.ppt)
    Lecture 2: Use of profiles (PSSMs) to find motifs in biomolecular sequences     (lecture.pdf  lecture.ppt)

Week 14:
    Lecture 1: Introduction to Markov Chain Monte Carlo (also see 2000 lectures, week 7)     (lecture.pdf )
    Lecture 2: SNP haplotype reconstruction     (lecture.pdf  lecture.ppt)

Week 15:
    Lecture 1: Human SNP haplotypes     (lecture.pdf  lecture.ppt)
    Lecture 2: Using human SNPs to map disease genes     (lecture.pdf  lecture.ppt)

Week 16:
    Lecture 1: Cancelled.    
    Lecture 2: Introduction to Affymetrix GeneChip data     (lecture.pdf  lecture.ppt)

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