Subject assesses the relationships between sequence, structure, and function in complex biological networks as well as progress in realistic modeling of quantitative, comprehensive functional-genomics analyses. Topics include: algorithmic, statistical, database, and simulation approaches; and practical applications to biotechnology, drug discovery, and genetic engineering. Future opportunities and current limitations critically assessed. Problem sets and project emphasize creative, hands-on analyses using these concepts.

Seminar covering topics of current interest in biology. Includes reading and analysis of research papers and student presentations. Contact Biology Education Office for topics. This course is one of many Advanced Undergraduate Seminars offered by the Biology Department at MIT. These seminars are tailored for students with an interest in using primary research literature to discuss and learn about current biological research in a highly interactive setting. To understand and treat any disease with a genetic basis or predisposition, scientists and clinicians need effective ways of manipulating the levels of genes and gene products. Conventional methods for the genetic modification of many experimental organisms are technically demanding and time consuming. Just over 5 years ago, a new mechanism of gene-silencing, termed RNA interference (RNAi), was discovered. In addition to being a fascinating biological process, RNAi provides a revolutionary technology that has already changed the way biomedical research is done and that may even prove useful for genetic interventions in a clinical context. In this course, students learn how RNAi was discovered, how it works, and what its physiological relevance might be. How RNAi can be harnessed to modulate gene expression and perform genetic screens, both in cells and in various organisms is also covered. Finally, this course examines the first attempts to use RNAi for the treatment of models of human diseases in experimental animals.

This is a seminar based on research literature. Papers covered are selected to illustrate important problems and approaches in the field of computational and systems biology, and provide students a framework from which to evaluate new developments. The MIT Initiative in Computational and Systems Biology (CSBi) is a campus-wide research and education program that links biology, engineering, and computer science in a multidisciplinary approach to the systematic analysis and modeling of complex biological phenomena. This course is one of a series of core subjects offered through the CSB Ph.D. program, for students with an interest in interdisciplinary training and research in the area of computational and systems biology.