Comp/Stat 470: From sequence to structure: Module II




Software resources


Hidden Markov Models

The classic paper is A tutorial on hidden Markov models and selected applications in speech recognition by Lawrence Rabiner, in the Proceedings of the IEEE, 77:2(257-286), 1989.

What you need to know about HMMs:

Computational genefinding using HMMs

Check the genefinding web site to get at the latest list of gene finders, data sets, and bibliography.

Reviews of genefinding

Methods of genefinding

Ab-initio Methods
Comparative Methods
Evaluating genefinding programs

Other approaches to genefinding

The chromosome 22 page is here.

Supervised learning

I will cover two families of supervised learning methods: discriminative models exemplified by support vector machines, and characteristic models exemplified by naive Bayes. I will also cover techniques for feature selection in the context of microarray data analysis. A Matlab based toolbox to experiment with these methods is here.

Support vector machines

SVMs for molecular classifications of cancer from gene expression data

Learning Bayesian networks

Learning Bayesian networks: theory

Background reading on genetic networks

Inferring regulatory networks from genomic and proteomic data

Bayesian network software

Other useful software and data for exploring metabolic networks and gene expression data
Last modified: Sun Jan 4 21:33:49 CST 2009