16:118:405Differential Equations in Biology (3) Models for biological processes based on deterministic ordinary and partial differential equations. Topics include stability, bifurcations, periodic phenomena, transport, and diffusion. Sontag. Prerequisites: Differential equations and linear algebra. |
16:118:503Introduction to BIOMAPS: Biology at the Interface with the Mathematical and Physical Sciences (3) Introduction to the phenomena ranging from molecular interactions to biological behavior at the level of cells, tissues, and organisms. Ruckenstein. Prerequisites: Linear algebra; calculus; and a good biology, chemistry, and physics background at the high school level. |
16:118:505Mathematical Foundations for Biology (3) This is a remedial course focusing on differential equations, Fourier and Laplace transforms, and stochastic processes for students interested in quantitative biology. Prerequisites: Calculus, some undergraduate exposure to ODEs, linear algebra, and basic probability. |
16:118:507Physics of Living Matter (3) Review of physical phenomena that determine the properties of biological molecules, molecular assemblies, and fundamental biological processes. Shraiman. Prerequisites: Linear algebra, differential equations, thermodynamics, and classical physics (at the junior level). |
16:118:509Biophysical Chemistry (3) Principles of biomacromolecular structure and dynamics including methods for representing and visualizing these molecules; biophysical methods; and methods for studying enzyme kinetics and protein-ligand binding. Introduction to various bioinformatics resources. Baum, Berman, Ebright. Prerequisite: Permission of instructor. |
16:118:511Modeling of Biomolecular Networks: An Introduction to Systems Biology (3) Focuses on a systems approach to biomolecular processes including the ideas, mathematical language, and modeling techniques used to describe the main mechanisms of transferring and processing of biological information. Sengupta. Prerequisites: Differential equations, linear algebra, probability and statistics; good chemistry/biology background at the high school level. |
16:118:513Molecular Simulations in Computational Biology (3) Focuses on molecular modeling and simulations of biological macromolecules including proteins and nucleic acids, molecular dynamics and Monte Carlo methods, and solvation. Computer simulations and exercises are an integral part of the course. Levy, Olson. Prerequisites: Advanced undergraduate courses in physical chemistry or physics. |
16:118:515Statistical Methods in Bioinformatics (3) Broadly applicable, modern statistical tools particularly important in modeling and interpreting noisy bioinformatics data. Jornsten. Prerequisites: Linear algebra and calculus. |
16:118:520Algorithmic Bioinformatics: A Computer Science Perspective (3) Advanced introduction to computational molecular biology covering sequence comparison, phylogeny, gene finding, comparative genomics and genome rearrangements, and haplotype inference; focuses on analyzing the complexity and efficiency of computational methods. Farach-Colton. Prerequisite: Basic analysis of algorithms course. |
16:118:601Protein Physics (3) Advanced introduction to protein folding, binding, and structure prediction including equilibrium and kinetic aspects of protein folding and binding, classification of protein folds, and structure prediction from sequence. Levy. Prerequisite: Permission of instructor. |
16:118:602Probabilistic Graphical Models (3) Advanced introduction to probabilistic graphical models, from Bayesian networks to factor graphs. Modeling techniques and advanced inference and learning algorithms, methods particularly relevant to current bioinformatics research. Pavlovic. Prerequisites: Knowledge of probability and random processes. |
16:118:603Regulation of Gene Transcription (3) Broad review of the regulation of gene transcription combining biophysics, structural biology, systems biology, bioinformatics, and control theory points of view. Prerequisite: Permission of instructor. |
16:118:605Pattern Formation in Biology: Signal Transduction, Biomolecular, and Genetic Networks in Development (3) Combines a molecular genetics description with quantitative modeling and physical view of pattern formation. Topics include robustness in genetic networks, limb regeneration, cell survival and death in development. Prerequisite: Permission of instructor. |
16:118:611Complex Systems: Physical Reality and Mathematical Models (3) Deterministic equations and probabilistic ideas from statistical mechanics will be used to describe organized behavior emerging from many interacting simple entities. Complex systems include the brain and chemical phase transitions. Lebowitz. Prerequisites: Familiarity with statistical mechanics and/or probability theory and dynamical systems theory. |
16:118:613Selected Math Topics in Physiology and Medicine (3) Mathematical modeling of selected biological phenomena and systems. Cellular homeostasis, regulation of cell function, cardiac rhythmicity, and hormone physiology are potential topics. Sontag. Prerequisite: Elementary differential equations or permission of instructor. |
16:118:616Special Topics in Quantitative Biology (3) Prerequisite: Permission of instructor. |
16:118:621,622Laboratory Rotation in BIOMAPS Institute Laboratories (1-2 BA,1-2 BA) Introduction to the techniques of BIOMAPS research through participation in research projects of selected members of the graduate faculty. Enrollment restricted to Ph.D. students in the BIOMAPS graduate program. No more than a total of 3 credits of laboratory rotation can be earned. |
16:118:701,702BIOMAPS Institute Research (BA,BA) |
