CS598 SS Probabilistic Methods for Biological Sequence Analysis (Spring 2009)

Schedule (tentative)

(01/20) Basic molecular biology: Proteins, DNA, Genes, Transcription, Translation, Transcriptional Regulation, Genome. Powerpoint Slides
(01/22,01/27) Basic probability and statistics: Bayes rule, Random variables, Expectation and moments, Discrete distributions, Continuous distributions, Likelihood maximization, Hypothesis testing, Markov Chains, Sampling, Entropy. PDF Slides
(01/27,01/29) Bayesian Inference , priors, practical priors, likelihood. (BB 2.3, DEKM 11.1) Example: Single die model with counts (BB 3.1). Powerpoint slides (Slides courtesy of Jin Tae Kwak.)
(01/29) Parameter estimation: Gradient Descent (BB 4.3), Expectation Maximization (DEKM 11.6). PDF slides (Slides courtesy of Charles Blatti.)
(02/03) Sampling: MCMC & detail balance, Metropolis-Hastings, Gibbs sampling. (DEKM 11.4). Powerpoint slides (Slides courtesy of Thyago Duque.)

(02/05,02/10) Scoring functions (DEKM 2.2). N-W and S-W and affine gap penalties. Significance of scores: Bayesian and Extreme value distribution (DEKM 2.7, DEKM 11.1, EG 6.3, EG 2.11)
(02/12) Paper presentation (Pritish Jetley): 1. "MCALIGN: stochastic alignment of noncoding DNA sequences based on an evolutionary model of sequence evolution." - Keightley and Johnson. Genome Res. 2004. and 2. "MCALIGN2: Faster, accurate global pairwise alignment of non-coding DNA sequences based on explicit models of indel evolution." - Wang, Keightley and Johnson. BMC Bioinformatics 2006.
(02/17) Paper presentation (Siva Theja Malguri). "Evolutionary HMMs: a Bayesian approach to multiple alignment" - Holmes and Bruno. Bioinformatics 2001. PPT

(02/19) Paper presentation (Chris Schlosberg) : "A statistical method for finding transcription factor binding sites." - Sinha and Tompa, ISMB 2000. Powerpoint Slides
(02/24) Paper presentation (Arash): Detecting subtle sequence signals: a Gibbs sampling strategy for multiple alignment - Lawrence et al. Science 1993.
(02/26) Paper presentation (Jia-yu): Probabilistic clustering of sequences: Inferring new bacterial regulons by comparative genomics - Nimwegen et al. PNAS 2002. PDF slides

(03/03) Paper presentation (Yi-shuen): A probabilistic method to detect regulatory modules. Sinha et al. Bioinformatics 2003.

(03/12,03/17) Evolution models (DEKM 8.1 - 8.3), calculating likelihood of alignment, reversibility, Metropolis algorithm for phylogenetic tree construction (DEKM 8.4), evolutionary models with gaps (DEKM 8.5).
(03/19) Paper presentation (Hlaing): Combining phylogenetic and hidden Markov models in biosequence analysis. Siepel & Haussler. Proc. 7th Annual Int'l Conf. on Research in Computational Biology (RECOMB '03).
(03/31) Paper presentation (Guest lecturer Jaebum Kim): Indelign: a probabilistic framework for annotation of insertions and deletions in a multiple alignment-- Jaebum Kim and Saurabh Sinha. Bioinformatics 2007. http://bioinformatics.oxfordjournals.org/cgi/content/abstract/23/3/289. Powerpoint
(04/02) Paper presentation (Oscar): Improved techniques for the identification of pseudogenes. Coin & Durbin. Bioinformatics, 20 Suppl 1:I94-I100, 2004. Powerpoint

(04/07, 04/09, 04/14, 04/16) Wright Fisher model, random drift, with selection only, with mutations only, coalescence theory. Directional and Balancing Selection. Non-constant Population Size. Recombination.

(04/21) BLAST statistics.
(04/23) BLAST statistics.
(04/28) Module finding with advanced evolutionary models: Xu Ling
(04/30) Thermodynamic model-based regulatory sequence analysis: Xin He. Powerpoint