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Course Criteria
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4.00 Credits
Details the molecular life cycles of viruses that infect mammalian cells. Topics to be covered include disease pathogenesis, immune evasion mechanisms, vaccination, and genetic immunization vectors.
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4.00 Credits
Survey of principles and patterns of animal behavior. Covers classical ethological research of Lorenz and others and modern research on the molecular basis of behavior, especially in model systems. Behaviors studied include reproductive behavior, rhythmic behavior, learning and memory, and feeding behavior.
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4.00 Credits
Introductory survey of neuronal plasticity and the principles of neuroanatomy, pharmacology, and development of the brain and spinal cord. Presents various forms of plasticity from regeneration to neuronal transplantation. Topics include dynamic instability, addiction, depression, hibernation, spinal injury, and Alzheimer's disease. Covers the role of neurotransmitters and growth factors in regulating brain plasticity. Stresses interactions between neurons, astroglial cells, and other nonneuronal cells. Summarizes animal and human studies of functional and structural recovery.
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4.00 Credits
In-depth study of experimental genetics from Mendel to the present, emphasizing methods and data by which genetic principles were developed and the genetic approach to biological research. Covers classic experiments on patterns of inheritance, chromosomes and genetic linkage, genetic variability, mutagenesis, DNA as the genetic material, and the nature of the genetic code. Special topics from both classic and recent literature include (but are not limited to) genetic screens, epistasis analysis, suppressors/enhancers, and mosaic analysis.
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4.00 Credits
The recent explosion in the availability of genomewide data such as whole genome sequences and microarray data led to a vast increase in bioinformatics research and tool development. Bioinformatics is becoming a cornerstone of modern biology, especially in fields such as genomics. It is thus crucial to understand the basic ideas and to learn fundamental bioinformatics techniques. The emphasis of this course is on developing not only an understanding of existing tools but also the programming and statistics skills that allow students to solve new problems in a creative way.
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4.00 Credits
Introduction to genomic methods for acquiring and analyzing genomic DNA sequences. Topics: genomic approaches to determining gene function, including determining genome-wide expression patterns; the use of genomics for disease-gene discovery and epidemiology; the emerging fields of comparative genomics and proteomics; and applications of genomics to the pharmaceutical and agbiotech sectors. Throughout the course, the computational methods for analysis of genomic data are stressed.
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4.00 Credits
Explores the genetic and genomic mechanisms underlying evolutionary change. Emphases are on complex trait evolution and its quantitative analysis, and the impact of modern mapping and genomic techniques on evolutionary biology. Topics include, but are not limited to, the genetics of adaptation and character regression; the evolution of complex characters and traits such as organ systems, the senses, and patterns of behavior; and methods for the study of quantitative trait locus (QTL) variation and multifactorial systems.
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4.00 Credits
This course introduces fundamental methods of analyzing large data sets from genomics experiments. Through a combination of lectures, hands-on computational training, and in-depth discussions of current scientific papers, students learn the conceptual foundations of basic analytical methods, the computational skills to implement these methods, and the reasoning skills to read critically the primary literature in genomics. Analysis focuses on data from genome-wide studies of gene expression using microarrays and from genome-wide studies of molecular interactions. Methods covered include clustering, multiple-hypothesis testing, and network inference. A large part of the course is dedicated to students completing an individual project that is tailored to meet their background and training.
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4.00 Credits
This course develops the biophysical approach to modeling biological systems, applied to classic problems of molecular biology, as well as to systems of recent interest. The course is organized in a bottomup way, beginning with models of cooperativity in binding and of promoter recognition and activation, proceeding through models of simple and complex networks, and working toward a population-level description of various systems. Diverse biological examples are presented to illustrate key concepts in biophysical modeling.
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4.00 Credits
Discussion of topics of medical importance using mathematics as a tool: control of the heart, optimal principles in the lung, cell membranes, electrophysiology, countercurrent exchange in the kidney, acid-base balance, muscle, cardiac catheterization, and computer diagnosis. Material from the physical sciences and is introduced and developed.
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