Courses

Students will learn how to read, present, and critique primary research publications in bioinformatics. Journal club participants will present high-impact recent journal publications selected by course instructors and learn how to read the paper, write critiques, and organize analysis insights into review papers. Students must show evidence of prior preparation prior to journal clubs and write critiques to show comprehension of the topics throughout the semester.

Human evolution and primatology; race; human genetics. Tasks performed by physical anthropologists.

Advanced Biological Anthropology Human evolution, primatology, race, human genetics. Tasks performed by physical anthropologists.

Discussion of current issues and trends in forensic DNA analysis, including advanced analysis of biological evidence samples.

Laboratory supplementing lecture (BY 502) through use of human specimens, models, and demonstrations.

Students study the mechanical analysis of motion as it applies to the human functional anatomy, linear and angular kinetics and kinematics, and application on data collection and evaluation in a semester research project.

The mathematical and pharmacokinetic relationships between physical and chemical properties of a drug and its dosage form and biological effects.

Topics include: computer data analysis and simulation, first and second laws of thermodynamics, free energy and equilibrium, calorimetry, protein stability, binding and interactions, solution thermodynamics, electrolytes.

Advanced biophysical chemistry, including biochemical reaction kinetics, enzyme catalysis, quantum mechanics, statistical thermodynamics, spectroscopy, including UV-VIS, fluorescence, circular dichroism, NMR, and Structure determinations. An emphasis is placed on the current research literature.

This course aims at introducing a range of powerful statistical methods applicable to many research problems in Biology and indispensable to the toolbox of researchers, including generalized linear models, linear mixed-effect models, and model selection. In addition, the course will develop the student's ability to manipulate, analyze, and visualize real-world complex data sets using the statistical software R.