MCP 156: How Cells Work: Energetics, Compartments, and Coupling in Cell Biology (MCP 256)
Open to graduate and medical students, and advanced undergraduates. Dynamic aspects of cell behavior and function, including cellular energetics, homeostasis, heterogeneity of membranes, structure and function of organelles, solute and water transport, signaling and motility. Emphasis is on the principles of how coupling of molecular processes gives rise to essential functions at the cellular level. Mathematical models of cell function. Student presentations.
MCP 200: Cardiovascular Physiology
Offered jointly with the Department of Medicine. Lectures, small group instruction, clinical presentations, and lab demonstrations of normal and disordered human cardiovascular physiology. Prerequisite: understanding of general biochemistry.
MCP 216: Genetic Analysis of Behavior (NBIO 216)
Advanced seminar. Findings and implications of behavioral genetics as applied to invertebrate and vertebrate model systems. Topics include biological clocks, and sensation and central pattern generators. Relevant genetic techniques and historical perspective. Student presentation.
MCP 256: How Cells Work: Energetics, Compartments, and Coupling in Cell Biology (MCP 156)
Open to graduate and medical students, and advanced undergraduates. Dynamic aspects of cell behavior and function, including cellular energetics, homeostasis, heterogeneity of membranes, structure and function of organelles, solute and water transport, signaling and motility. Emphasis is on the principles of how coupling of molecular processes gives rise to essential functions at the cellular level. Mathematical models of cell function. Student presentations.
MCP 287: Connectomes
(Same as
PSYCH 287) Neural circuitry can be measured over a huge range of spatial scales, from sub-synaptic to whole brain connectomes. The methods used to measure these scales differ enormously, and scientists working at one scale should be able to understand and communicate with those measuring at other scales. Reviews methods, principal results, and ideas for integrating findings across scales by large-scale computation modeling.
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