MCB112: Biological Data Analysis (Fall 2018)


week 00: Wed 5 Sept
welcome and preview
[Lecture notes] [Example Jupyter notebook page] [Section notes]

week 01: Mon/Wed 10/12 Sept
molecular biology of genes, gene expression, and RNA-seq
[Lecture notes] [Section notes - Python] [Section notes - Molecular biology]
[Homework]

week 02: Mon/Wed 17/19 Sept
RNA-seq read mapping -- doing controls on new programs -- kallisto -- the unix command line
[Lecture notes]
[Homework]

week 03: Mon/Wed 24/26 Sept
data exploration and visualization -- subsampling data -- tidy data

week 04: Mon/Wed 1/3 Oct
probability, likelihood, and inference -- Laplace and Bayes

week 05: Wed 10 Oct
P-values and statistical significance
(Monday is a holiday, Indigenous People's Day)

week 06: Mon/Wed 15/17 Oct
mixture models -- K-means -- expectation maximization

week 07: Mon/Wed 22/24 Oct
regression -- regression as probabilistic inference

week 08: Mon/Wed 29/31 Oct
inferring hidden variables -- multimapped reads and mRNA isoform expression estimation -- expectation maximization again

week 09: Mon/Wed 5/7 Nov
cluster analysis -- non-negative matrix factorization

week 10: Mon/Wed 12/14 Nov
inference and hypothesis testing -- differential expression analysis
(Monday is Veterans' Day, but Harvard classes are in session)

week 11: Mon 19 Nov
work patterns in computational research -- artifacts, batch effect
no pset - Thanksgiving weekend
(Wednesday-Sunday are holidays, Thanksgiving)

week 12: Mon/Wed 26/28 Nov
dimensionality reduction -- principle component analysis

week 13: Mon/Wed 3/5 Dec
t-SNE

 Fini! Harvard reading period, finals begin -- no further assignments |