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Dept. of Microbiology & Immunology University of Tennessee, Memphis
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EXTRA-DEPARTMENTAL COURSES From the Department of Biochemistry Proteins, Energy and Metabolism This course is designed to provide a foundation in biochemistry. Included among the topics covered are: biochemical thermodynamics, enzyme kinetics, biological macromolecules; chemistry and metabolism of amino acids, carbohydrates, lipids, purines and pyrimidines; central metabolic pathways including their regulation; signal transduction. Prerequisites for the course include organic chemistry and physical chemistry is recommended. Proteins & Enzymes An advanced course dealing with the structure of proteins, and their intra- and inter-molecular interactions when participating in enzyme catalysis and the regulation of cellular processes. The above foundation course in biochemistry is a prerequisite. From the Department of Biostatistics and Epidemiology Biostatistics for the Health Sciences The first semester material includes descriptive statistics, estimation, and one and two sample hypothesis testing, including paired and unpaired situations. Instruction includes assisting the student to attain mastery-level skill in data entry and use of SAS software for statistical analysis on data on the UT VAX. Biostatistics for Observational Data This course presents fundamental statistical concepts such as random variable sand hypotheses testing. A discussion of contingency tables leads to survival analysis, proportional hazards and binary logistic regression. This course is designed for individuals who wish to use statistics in their research, but only have a single semester to devote to the acquisition of statistical knowledge. Emphasis on statistics which are used in studies of chronic diseases. Fundamentals of Epidemiology The course introduces the basis principles and methods of epidemiology and demonstrates their applicability in the field of public health. Topics to be covered include the historical perspective and epidemiology, measures of disease occurrence and of association, hospital epidemiology, disease screening, casual inference, and study design. Students will use SAS to analyze data from actual epidemiological studies and will learn to critically interpret the epidemiologic literature.
From the Department of Computer Sciences
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