Objectives

The goal of this course will be to provide students with working knowledge of bioinformatics and its applications through a combination of lectures describing applications in particular areas and a mandatory course project in which students will develop an application addressing an important problem in applied bioinformatics. Examples would include integrating the results of a variety of gene prediction programs and sequence similarity searches to annotate a genomic sequence, mapping genomic or expression data to metabolic pathways, the creation of new tools for the analysis of gene expression data, or the development of an approach to integrate genomic and genetic data.

Description

This course will focus on applications of many of the tools and techniques introduced in other courses in this program to lead students through a bioinformatics as it relates to genomic applications, starting with gene predictions and genome annotation, analysis of expressed sequence tags, comparative genomics, metabolic pathway analysis, and functional approaches using microarrays and proteomics, including class discovery and class predictions. Class presentations will be primarily given by the course instructor with additional one hour lectures from a variety of speakers. Possible outside lecturers and topics include Jonathan Eisen of The Institute for Genomic Research speaking on comparative genomics, Chris Stoeckert of the University of Pennsylvania speaking on the use of ontologies in genomic analysis, John Weinstein of the National Cancer Institute speaking on literature mining, and Tara Matise of Rutgers University speaking on genetic mapping.

Instructor

John Quakenbush (TIGR)

Credits: 3