Courses

REQUIRED COURSES 1st YEAR CURRICULUM:

HGEN 47000 Human Genetics I. Ober, Nobrega, Waggoner.

This course covers classical and modern approaches to studying cytogenetic, Mendelian, and complex human diseases. Topics include chromosome biology, single gene and complex diseases, non-Mendelian inheritance, cancer genetics, human population genetics, and genomics. The format includes lectures and student presentations. Autumn.

MGCB 31400 Genetic Analysis of Model Organisms. Bishop, Ferguson, Malamy and Moskowitz.

Coverage of the fundamental tools of genetic analysis as used to study biological phenomena. Topics include genetic exchange in prokaryotes and eukaryotes, analysis of gene function, and epigenetics. Autumn.

HGEN 46900 Human Variation and Disease. Di Rienzo, Novembre.

This course focuses on principles of population and evolutionary genetics and complex trait mapping as they apply to humans. It will include the discussion of genetic variation and disease mapping data. Spring.

HGEN 31900 Introduction to Research.

Lectures on current research by departmental faculty and other invited speakers. A required course for all first-year graduate students in Human Genetics. Autumn, Winter.

HGEN 40300 Non-Thesis Research.

Laboratory rotations, and all research prior to passing the Qualifying Examination. Autumn, Winter, Spring, Summer.

BSDG 55100 Responsible, rigorous and reproducible conduct of research: R3CR.

Required of all First Year BSD grad students. Winter.

CHOOSE AT LEAST ONE OF THE FOLLOWING TO FULFILL 1 COURSE REQUIREMENT:

HGEN 47100  Introductory Statistical Genetics. He, Im

This course focuses on genetic models for complex human disorders and quantitative traits. Topics covered also include linkage and linkage disequilibrium mapping genetic models for complex traits, and the explicit and implicit assumptions of such models. Winter.

OR

HGEN 31100 Evolution of Biological Molecules. Thornton,Drummond.

Introductory graduate-level course connects evolutionary changes imprinted in genes and genomes with the structure, function and behavior of the encoded protein and RNA molecules. Central themes are the mechanisms and dynamics by which molecular structure and function evolve, how protein/RNA architecture shapes evolutionary trajectories, and how patterns in present-day sequence can be interpreted to reveal the interplay data of evolutionary history and molecular properties. Winter.

OR

HGEN 48600 Fundamentals of Computational Biology: Models and Inference. Novembre, Stephens.

Covers key principles in probability and statistics that are used to model and understand biological data. There will be a strong emphasis on stochastic processes and inference in complex hierarchical statistical models. Topics will vary but the typical content would include: Likelihood-based and Bayesian inference, Poisson processes, Markov models, Hidden Markov models, Gaussian Processes, Brownian motion, Birth-death processes, the Coalescent, Graphical models, Markov processes on trees and graphs, Markov Chain Monte Carlo. PQ: STAT 244 or equivalent. Winter.

ECEV 35600 Population Genetics I. Wu, Kreitman, Steinrücken.

Examines the basic theoretical principles of population genetics, and their application to the study of variation and evolution in natural populations. Topics include selection, mutation, random genetic drift, quantitative genetics, molecular evolution and variation, the evolution of selfish genetic systems, and human evolution. Winter.

OR

HGEN 47300 Genomics and Systems Biology. Gilad.

This lecture course explores technologies for high-throughput collection of genomic-scale data, including sequencing, genotyping, gene expression profiling, and assays of copy number variation, protein expression and protein-protein interaction. In addition, the course will cover study design and statistic analysis of large data sets, as well as how data from different sources can be used to understand regulatory networks, i.e., systems. Statistical tools that will be introduced include linear models, likelihood-based inference, supervised and unsupervised learning techniques, methods for assessing quality of data, hidden Markov models, and controlling for false discovery rates in large data sets. Readings will be drawn from the primary literature. Evaluation will be based primarily on problem sets. Spring.

OR

MGCB 31300 Molecular Biology II. Ruthenberg/Staley.

Eukaryotic Gene Expression. Transcription and Posttranscriptional Regulation. Analysis of regulatory pathways and mechanisms involved in the control of eukaryotic gene activity. Spring.

OR

DVBI 36400 Developmental Mechanisms. Ferguson, Fehon. 

This course provides an overview of the fundamental questions of developmental biology, with particular emphasis on the genetic, molecular and cell biological experiments that have been employedto reach mechanistic answers to these questions. Topics covered will include formation of the primary body axes, the role of local signaling interactions in regulating cell fate and proliferation, the cellular basis of morphogenesis and stem cells. Winter.

ADDITIONAL ELECTIVE COURSES TO CHOOSE FROM TO FULFILL 4 COURSES:

HUMAN GENETICS

HGEN 39900 Readings in Human Genetics. HG Faculty.

A course designed by students and faculty member. All reading courses must be approved by the Curriculum Committee prior to registration. See page 8 for our policy onreading courses. Autumn, Winter, Spring, Summer

HGEN 47400 Introduction to Probability and Statistics for Geneticists. Abney.

This course is an introduction to basic probability theory and statistical methods useful for people who intend to do research in genetics or a similarscientific field. Topics include random variable and probability distributions, descriptive statistics, hypothesis testing and parameter estimation. Problem sets and tests will include both solving problems analytically and analysis of data usingthe R statistical computing environment. Autumn

HGEN 48800 Fundamentals of Computational Biology: Algorithms and Applications. He.

This course will cover principles of data structure and algorithms, with emphasis on algorithms that have broad applications in computational biology. The specific topics may include dynamic programming, algorithms for graphs, numerical optimization, finite-difference, schemes, matrix operations/factor analysis, and data management (e.g. SQL, HDF5). We will also discuss some applications of these algorithms (as well as commonly used statistical techniques) in genomics and systems biology, including genome assembly, variant calling, transcriptome inference, and so on. Spring

HGEN 36400 Molecular Phylogenetics. Thornton.

In this course you will learn the fundamental concepts and current techniques for inferring evolutionary relationships from gene sequence data and testing hyptheses about molecular evolution using those phylogenies as a scaffold. We will cover the theoretical basis of phylogenetic methods in evolutionary and statistical history, including the justifications and applications for maximum parsimony, evolutionary distance, maximum likelihood, and Bayesian analysis. We will discuss cases in which these methods have been applied to understand the evolution of taxa, genes and diseases. Offered alternate (even) Spring.

BIOCHEMISTRY AND MOLECULAR BIOLOGY

BCMB 30400 Protein Fundamentals. Keenan, Koide, Kossiakoff. 
The course covers the physico-chemical phenomena that define protein structure and function. Topics include: 
1) the interactions/forces that define polypeptide conformation

2) the principles of protein folding, structure and design

3) the concepts of molecular motion, molecular recognition, and enzyme catalysis.

PQ: BMB 30100, which may be taken concurrently, or equivalent. Autumn.

DEVELOPMENTAL BIOLOGY

DVBI 35600 Vertebrate Developmental Genetics. Prince.

This advanced-level course combines lectures, student presentations, and discussion sections. It covers major topics in the developmental biology of vertebrate embryos (e.g., formation of the germ line, gastrulation, segmentation, nervous system development, limb patterning, organogenesis). The course makes extensive use of the current primary literature and emphasizes experimental approaches including embryology, genetics, and molecular genetics. Spring.

ECOLOGY AND EVOLUTION

ECEV 35901 Genomic Evolution. Long.

Canalization, a unifying biological principle first enunciated by Conrad Waddington in 1942, is an idea that has had tremendous intellectual influence on developmental biology, evolutionary biology, and mathematics. In this course we will explore canalization in all three contexts through extensive reading and discussion of both the classic and modern primary literature. We intend this exploration to raise new research problems which can be evaluated for further understanding. We encourage participants to present new ideas in this area for comment and discussion.Autumn.

MOLECULAR GENETICS AND CELL BIOLOGY

MGCB 31600 Cell Biology I. Turkewitz, Glick.

Eukaryotic protein traffic and related topics, including molecular motors and cytoskeletal dynamics, organelle architecture and biogenesis, protein translocationand sorting,compartmentalization in the secretory pathway, endocytosis and exocytosis, and mechanisms and regulation of membrane fusion. Autumn.

MGCB 31200. Molecular Biology I. Rothman-Denes, Lucia.

Nucleic acid structure and DNA topology; methodology; nucleic-acid protein interactions; mechanisms and regulation of transcription in eubacteria, and of replication in eubacteria andeukaryotes; mechanisms of genome and plasmid segregation in eubacteria. Winter

MGCB 31700 Cell Biology II. Glotzer, Kovar.

Chromatin structure and its role in transcription communication between nucleus and cytoplasm, translation, protein folding and assembly, molecular chaperones, elements of signaltransduction, homeostasis, growth control and the cell cycle, cytoarchitecture, cell adhesion and migration. Winter.

MGCB 32000 Quantitative Analysis of Biological Dynamics, Munro, Rust.

This course covers quantitative approaches to understanding biological organization and dynamics at molecular, sub-cellular and cellular levels. A key emphasis is on the use of simple mathematical models to gain insights into complex biological dynamics. We also will cover modern approaches to quantitative imaging and image analysis, and methods for comparing models to experimental data. A series of weekly computer labs will introduce students to scientific programming using Matlab and exercise basic concepts covered in the lectures. Spring.

MICROBIOLOGY

MICR 34000 Bacterial Pathogenesis. Missiakas, Schneewind, Shuman.

This course focuses on the genetics and molecular biology of bacterial pathogens with emphasis on host-pathogen interactions. The course will cover topics rangingfrom toxin production and secretion to evasion of host-responses and antibiotic resistance. Current techniques and discoveries will be covered in a paper-based discussion section. Winter.

STATISTICS

STAT 24400-24500 Statistical Theory and Methodology I, II. Barber/ Wu Wei. Principles and techniques of statistics with emphasis on the analysis of experimental data. First quarter: Discrete and continuous probability distributions,transformation of random variables; principles of inference including Bayesian inference, maximum likelihood estimation, hypothesis testing, likelihood-ratio tests, multinomial distributions and chi-square tests. Second quarter: Multivariatenormal distributions and transformations, Poison processes, data analysis, t-tests, confidence intervals, analysis of variance and regression analysis. Autumn, Winter.

STAT 35500 Statistical Genetics. McPeek. This is an advanced course in statistical genetics. Prerequisites are Human Genetics 47100 and Statistics 24400 and 24500. Students who do not meet the prerequisites may enroll on a P/NPbasis with consent of the instructor. Prerequisites are either Human Genetics 47100 or statistics preparation at the level of Statistics 24400 and 24500. This is a discussion course and student presentations will be required. Topics varyand may include, but are not limited to, statistical problems in linkage mapping, association mapping, map construction, and genetic models for complex traits. Spring