This course will provide an introduction to key concepts in the genome sciences, using tools and concepts from computational biology and bioinformatics. Topics to be covered include genome structure, function, variation, and evolution. Students will learn computational and statistical methods for describing and quantifying various aspects of genome biology and will apply these tools to real world data. Prerequisite: Familiarity with molecular biology concepts such as DNA replication, transcription, and translation. No prior programming experience is required.
Quantitative understanding of biological systems through the application of physical principles. Course will emphasize topics that span multiple length and time scales, and different levels of biological organization. Two to four topics per semester, including possibly organismal motion from molecular processes to whole organisms, nervous systems from membrane channels to neuronal networks, noise in biology, novel biophysical technologies, etc. Prerequisite: Biology 201L, Mathematics 212 and 216 or equivalent, and calculus based introductory physics or permission of the instructors.
How theory and experimental techniques from physics can be used to analyze and understand biological structure and function, including chemical, mechanical, electrical, collective, and information-processing aspects. Prerequisites: Biology 201L and knowledge of statistical physics by taking either Physics 363 or Chemistry 311.
An exploration of how we have come to understand the relationships between genes and traits, with a focus on traits of biomedical importance. We explore how physiological systems biology can be used to understand the causal pathways by which genes affect traits. Examples will be taken largely from the biomedical literature with a focus on genetic diseases and the roles of genetic background and environment in determining how (and why) genes affect traits. Readings and class participation, short papers and oral presentations on research projects. Nijhout
Evolution of genes, gene families, and genomes and relation to their structure, function and history. Contemporary computer-based analysis of nucleic acid and protein evolution including: BLAST searches; sequence alignment; estimation of rates, patterns, types of substitution; interpreting evolutionary changes in structure-function relations; protein homology modeling; visualizing and annotating protein structure. Prerequisite: Biology 201L or consent of the instructor. One course.
Use of genetic sequence analysis to examine aspects of natural populations of humans and other organisms in the past and present. Topics include molecular phylogenetics; the origin, maintenance, and loss of major features of evolution; the evolutionary process at the molecular level; reconstruction of human origins and paleohistory; and genetic information in forensic studies. One course.
A first course in biological modeling. Emphasizes methods common to model building in general. Mathematica based lab develops and applies a high level programming language to simplify model building. Topics drawn from cell and molecular biology, molecular evolution, enzyme catalysis, biochemical pathways, population genetics, ecology, systems biology, and developmental biology. Prerequisite: Mathematics 103 or equivalent. One course.
A first course applying mathematics to biological problems. Topics drawn from cell and molecular biology, molecular evolution, enzyme catalysis, biochemical pathways, ecology, systems biology, and developmental biology. Prerequisite: Mathematics 212 or equivalent. One course.