Molecular Biophysics - Course Descriptions

Covers optical spectroscopy with emphasis on applications in biomedical research. including interaction of light and matter, absorption spectroscopies (UV/vis and infrared), fluorescence, and circular dichroism.

The basics of computational methods used to analyze protein sequences and structures. Topics include sequence similarity searches using profile-based tools, functional prediction, structure prediction and threading, homology modeling, energy-based simulations, protein classification, and evolutionary concepts: homology inference and tree reconstruction.

Principles of nuclear magnetic resonance (NMR), emphasizing its application to macromolecular structure determination. Topics include multidimensional NMR spectroscopy, including COSY, TOCSY and NOESY experiments, sequential assignments and structural analysis, practical methods and new developments in the field.  Recommended prerequisites:  Modern Methods in Structural Biology.

Overview of the basic principles governing protein structure and folding. Topics include stereochemical mechanisms by which protein secondary and tertiary structures are generated and stabilized, methods of prediction of tertiary structure from amino acid sequence, and the organization of folding motifs into protein structures. Instruction will be based on didactic material, discussion of the primary literature, and student projects utilizing computer graphics.

Computational Methods in the Biological Sciences            
TBA

Biocomputing and computational biology are synonyms that describe the use of computers and computational techniques to analyze biological systems, from individual molecules to organisms to higher-order systems. This course will cover the computational techniques used to access, analyze, and interpret the biological information in common types of biological databases and the biological questions that can be addressed by such methods, applicable to the study of the context of genes within the same genome and across different genomes, the study of molecular sequence data for the purpose of inferring the function, interactions, evolution, and structure of biological molecules, and the study of annotation and ontology.

Advances in biotechnology are making it possible to obtain massive amounts of data about the genetic information contained in living cells, the transmission of this information from parent to child, the changes in the information over evolutionary time, and the manner in which this information influences the chemical activity of cells. This course is an introduction to algorithmic techniques for the acquisition, analysis and interpretation of such data.

Provides students with a basic understanding of enzyme mechanism and enzyme kinetic analysis.  Topics to be covered include basic Michaelis-Menten kinetics, multisubstrate reactions and inhibitor studies ranging from the methods to analyze simple competitive inhibitors to suicide or tight binding inhibitors.  These principles will be illustrated for a series of classic well-characterized enzyme reactions.  Emphasis is placed on quantitative analysis through a series of problem sets and through reading and discussion of the primary literature.

The operation of the nervous and muscular systems rests upon the activities of a constellation ion channels, which mediate electrical signaling by action potentials, intracellular communication by electrical and chemical synaptic transmission, transduction of sensory stimuli, and the excitation-contraction coupling. Drawing upon the techniques of biophysics, biochemistry, and molecular biology, students in this course will consider the structures and functions of representative channels.

High-throughput methodologies are generating complex experimental data at an incredible rate. As a result, these developments are forcing a paradigm shift in how the result from biological experimentation are interpreted, in which computers are playing an increasingly important role. The increasing use of computers for data storage, data retrieval, and data analysis is leading to the evolution of two biological disciplines - bioinformatics and computational biology. In this course, we will use the gene expression microarray experimental platform as a model highthroughput methodology to examine how bioinformatics, statistics and computation are being used to support the discovery of new biomedical knowledge. In addition to didactic lectures and discussion, this class will include a series of hands-on workshops focused on the basic steps for microarray data processing.