Courses taught
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.