Course description and objectives: With the recent dramatic increase in many types of biological data due to the human genome project and other high-throughput projects, the scope of research in bioinformatics has expanded to a diverse range of topics including protein, DNA and RNA sequence analysis, microarray analysis, structural and functional predictions, gene finding and phylogeny reconstruction. This one semester course is intended to provide coverage of bioinformatics developments in the past two decades with an emphasis on topics of recent interest. By the end of this class, students are expected to have an in-depth knowledge of computational methods important in bioinformatics, and a thorough grasp of the underlying principles which would be adequate to evaluate and develop novel techniques in scenarios that may arise in the future.

Course description and objectives: Introduction to set theory and basic probability, population, sample, random variables, discrete distributions, continuous distributions, moments, bivariate and multivariate distributions , independence, covariance, distributions of functions of random variables. Will cover the essential features of one sample and two sample inference for discrete and continuous response data, with an emphasis on parametric methods.