Coursework

Bioinformatics Courses

BCB594 - Advanced Genome Informatics Applications of sequence models: codon usage; discrete and continuous models of nucleotide substitution; synonymous and nonsynonymous nucleotide substitutions. Basic methods in molecular phylogeny: phylogenetic trees; distance matrix methods; maximum parsimony methods; maximum likelihood methods. Advanced sequence models: Random walks; score-based sequence analysis; Interpolated Markov Models; Markov Random Fields; applications to genome annotation; genome rearrangements. Hidden Markov Models: theory; training; applications to gene structure annotation, sequence alignment, and protein classification. DNA and protein motifs: weight matrices; word-based methods; EM algorithm, Gibbs sampling, and simulated annealing; Bayesian methods. Introduction to gene expression analysis, mRNA and protein expression data analysis, multiple comparisons.

BCB597 - Introductory Computational Structural Biology Mathematical and computational approaches to protein structure prediction and determination. Topics include molecular distance geometry, potential energy minimization, and molecular dynamics simulation.

STAT432 - Applied Probability Models Probabilistic models in biological, engineering and the physical sciences. Markov chains; Poisson, birth-and-death, renewal, branching and queing processes; applications to bioinformatics and other quantitative problems.

BCB593 - Workshop in Bioinformatics and Computational Biology Current topics in bioinformatics and computational biology research. Lectures by off-campus experts. Students read background literature, attend preparatory seminars, attend all lectures, meet with lecturers.

BCB565B - Professional Practice in Life Sciences: Intellectual Property and Industry Interaction This 8-hour, 0.5 credit module is specifically designed for students in the life sciences interacting with or anticipating interaction with industry. It covers topics such as: why and how universities interact with industry, assistance available for researchers working with industry, and the real meaning of terms such as intellectual property, freedom to operate, and confidentiality. It also covers research contracts and license agreements and how they impact university research. The focus will be on practical information that will help students successfully interact with industry both before and after graduation.

BCB565C - Professional Practice in Life Sciences: Life Science Ethics Many life scientists do research that is the focus of intense moral debate in our society. This module will approach current topics in bioethics from the perspective of the scientist. The aim of the module is to help prepare future scientists to participate in bioethical debates and to critically evaluate their own scientific activities from an ethical perspective. Students will participate in choosing the particular ethical topics that will be the focus of the course.

Computer Science Courses

ComS561 - Principles of Database Systems Database models. Algebraic, first order, and user-oriented query languages. Database schema design. Physical storage, access methods, and query processing. Transaction management, concurrency control, and crash recovery. Database security. Parallel and distributed databases, and special purpose databases. Data warehousing and data mining.

ComS672 - Advanced Topics in Computational Models of Learning Design, Analysis, and Application of Programs that Learn from Experience. Statistical, Syntactic, Information-Theoretic, Neural, Cognitive, and Evolutionary models. Automated learning of classification rules, programs, functions, relations, grammars, value functions, models, skills, and behaviors. Computational learning theory (PAC, Maximum Likelihood, Minimum Description Length and related frameworks). Learning from instances, induction, deduction, reinforcement, and exploration. Incremental, multi-task, multi-strategy learning. Selected applications in Scientific Data Analysis, Data-Driven Knowledge Discovery and Theory Refinement, Bioinformatics, Analysis and Control of Complex Dynamical Systems, Intelligent Agents and Multi-Agent Systems.

ME557 - Computer Graphics and Geometric Modeling Fundamentals of computer graphics technology. Data structures. Parametric curve and surface modeling. Solid model representations. Applications in engineering design, analysis, and manufacturing.

Biology/Genetics Courses

BBMB551 - Molecular Biophysics An examination of physical methods for the study of molecular structure and organization of biological materials, with emphasis on applications. Spectroscopy, hydrodynamic methods, nuclear magnetic resonance, and X-ray diffraction.

BBMB675 - Nucleic Acid Structure & Function Properties of nucleic acids; relationship of nucleic acid structure to function. Chemistry of nucleotides; the chemical reactivity of nucleic acids; analytical and separation methods; nucleases; sequence determination; synthesis of specific genes; nucleoproteins.

GEN411 - Molecular Genetics Molecular biology and cellular biochemistry with focus on systems-level analyses and high-throughput technologies. Review of basic cell structure and function; Principles of molecular genetics; Regulation of gene expression; Principles of cellular and developmental regulation, molecular evolution; Methods for high-throughput genomic, transcriptomic, metabolomic, structural genomic, and proteomic analyses.

BBMB542B - Introduction to Molecular Biology Techniques: Protein Techniques Includes fermentation, protein isolation and analysis, NMR and monoclonal antibody production.

BBMB542E - Introduction to Molecular Biology Techniques: Proteomics Includes two-dimensional electrophoresis, laser scanning, mass spectrometry, and database searching.

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