This hands-on course will focus on advanced algorithms and machine learning techniques for searching, classifying, analysing and modeling DNA, RNA and protein sequence data. It will also introduce techniques for analysing other kinds of genomics information such as data obtained from "gene chips". Techniques covered will include fast string searching, pairwise alignment, Bayesian learning methods, multiple alignment, simple Markov models, hidden Markov models, neural nets, decision trees, inductive logic programming, and support vector machines. Lab: Programming assignments involving modification and implementation of techniques covered in the lectures.