Chair, Professor CHARLES M. LOVETT, Jr.

Advisory Committee: Professors: ALTSCHULER, BAILEY, R. DE VEAUX, KAPLAN, LOVETT**, D. LYNCH, RAYMOND. Associate Professors: AALBERTS*, BANTA, SAVAGE*. Senior Lecturer: D. C. SMITH. Assistant Professors: GEHRING, HUTSON, TING.

Bioinformatics, genomics, and proteomics are rapidly advancing fields that integrate the tools and knowledge from biology, chemistry, computer science, mathematics, physics, and statistics in research at the intersection of the biological and informational sciences. Inspired by the enormous amount of biological data that are being generated from the sequencing of genomes, these new fields will help us pose and answer biological questions that have long been considered too complex to address. Research in genomics, proteomics, and bioinformatics will also significantly impact society affecting medicine, culture, economics, and politics.

The Bioinformatics, Genomics, and Proteomics curriculum involves faculty from the biology, chemistry, computer science, mathematics/statistics, and physics departments and was designed to provide students with an understanding of these revolutionary new areas of investigation. The introductory level courses, Computation and biology and Statistics for Biologists are accessible to all students interested in gaining familiarity with the power of genomic analysis. Students interested in graduate work in bioinformatics, genomics, and proteomics should take the core courses and five of the recommended courses. Interested students are also encouraged to participate in independent research with members of the advisory faculty as they explore the development of these new fields.

Core course:

Biology/Chemistry/Computer Science/Mathematics/Physics 319 Bioinformatics, Genomics, and Proteomics Laboratory

Computer Science/Biology 106 Life as an Algorithm

Recommended courses (in addition to the core course):

Biology 202 Genetics

Biology 206T Genomes, Transcriptomes and Proteomes

Biology 305 Evolution

Computer Science 134 Introduction to Computer Science

Computer Science 136 Data Structures and Advanced Programming

Computer Science 256 Algorithm Design and Analysis

Computer Science/INTR/Physics 315 Computational Biology

Statistics 101 or 201 Statistics

Related courses:

Biology 322 Biochemistry II-Metabolism

Chemistry 111 Fighting Disease: The Evolution and Operation of Human Medicine

Chemistry 321 Biochemistry I-Structure and Function of Biological Molecules

Philosophy 334 Philosophy of Biology

Physics 302 Statistical Physics

Statistics 231 Statistical Design of Experiments