Course Requirements

A minimum of 60 credits of coursework is required for the SM in Computational Biology and Quantitative Genetics. This includes a 17.5 credit ordinally graded core curriculum consisting of:

BIO 211  Regression and ANOVA (5 credits)
BIO 222  Basics of Statistical Inference (5 credits)
BIO 290  Introductory Methods in Bioinformatics (2.5 credits)
EPI 201  Introduction to Epidemiology Methods: 1 (2.5 credits)
EPI 249  Fundamentals in Molecular Biology (2.5 credits)

An additional ten credits comprised of all courses in either one of the two following tracks:

Statistical Genetics Track

EPI 293  Analysis of Genetic Association Studies (2.5 credits)
EPI 507  Genetic Epidemiology (2.5 credits)
EPI 511  Advanced Population and Medical Genetics (2.5 credits)
BIO 227  Fundamental Concepts in Gene Mapping (2.5 credits)

Computational Biology Track

BIO 506  Introduction to Computational Biology (5 credits)
BIO 508  Genomic Data Manipulation (5 credits)

All students will also participate in a one-semester, 5-credit research Genomic Analysis Practicum course, which requires students to design and complete an end-to-end analysis project under the guidance of a faculty specializing in computational biology, statistical genetics, network analysis, or genetic epidemiology.

Students with prior equivalent background to any of these courses or strong reasons to take a different course can request permission from the Director of Master’s Programs for a substitution of one or more of these required courses.

A minimum of 27.5 additional credits will come from the alternative track or the following list of elective courses:

BIO 210  Analysis of Rates and Proportions (5 credits)
BIO 212  Survey Research Methods in Community Health (2.5 credits)
BIO 214  Principles of Clinical Trials (2.5 credits)
BIO 223  Applied Survival Analysis (5 credits)
BIO 226  Applied Longitudinal Analysis (5 credits)
BIO 257  Advanced Statistical Genetics (5 credits)
BIO 283  Spatial Statistics for Health Research and Social Inquiry (5 credits)
BIO 287  Public Health Surveillance (2.5 credits)
BIO 503  Introduction to Programming and Statistical Modeling in R (1.25 credits)
BIO 504  Introduction to Geographical Information Systems using ArcGIS (1.25 credits)
BIO 505  Database Design and Use for Health Research (1.25 credits)
BIO 512  Introduction to Computational Biology and Bioinformatics (5 credits)
BIO 513  Advanced Computational Biology and Bioinformatics (5 credits)
BIO 514  Introduction to Data Structures and Algorithms (2.5 credits)
BIO 521  Introduction to Social and Biological Networks (5 credits)
EPI 201  Introduction to Epidemiology Methods: 1 (2.5 credits)
EPI 202  Elements of Epidemiologic Research: Methods 2 (2.5 credit)
EPI 203  Study Design in Epidemiologic Research (2.5 credits)
EPI 204  Analysis of Case-Control and Cohort Studies (2.5 credits)
EPI 221  Pharmacoepidemiology (2.5 credits)
EPI 222  Genetic Epidemiology of Diabetes (5 credits)
EPI 271  Propensity Score Analysis (1.25 credits)
EPI 288  Data Mining and Prediction (2.5 credits)
EPI 289  Causal Inference (2.5 credits)
ID 271  Advanced Regression for Environmental Epidemiology (2.5 credits)
RDS 280  Decision Analysis for Health and Medical Practices (2.5 credits)
RDS 282  Cost-Effectiveness and Cost-Benefit Analysis for Health Program Evaluation (2.5 credits)
RDS 285  Decision Analysis Methods in Public Health and Medicine (2.5 credits)
Biophysics 170  Quantitative Genomics (5 credits)
Biophysics 376  Functional and Computational Genomics studies of Transcription Factors and Cis Regulatory Elements (5 credits)
BMI701/702  Introduction to Biomedical Informatics (10 credits)
Statistics 121  Data Science (2.5 credits)
Statistics 183  Learning from Big Data (5 credits)

Other courses may also be acceptable to satisfy these 15 additional credits. Students are advised to consult with the Director of Master’s Studies to check prior to enrolling in alternative courses.