Interdisciplinary Grant in Biostatistics




Coursework for Biostatistics Ph.D. Students with an Emphasis on Quantitative Genomics

A Biostatistics Ph.D. student is required to satisfy all degree requirements as specified in the Department's Graduate Student Handbook. As part of their program, students with an emphasis in quantitative genomics are required to follow the program described below and satisfy the 10 credits for a cognate field in an area related to quantitative genomics. Students are expected to take at least one course in the category of Data Structures and Programming and one course in the category of Molecular Biology, Physiology, and Genetics. Through a careful selection of courses, most of the courses below will be useful towards satisfying Ph.D. degree requirements.

Required Core Courses:

  • BIST 230 Probability Theory and Applications I
  • BIST 231 Statistical Inference I
  • BIST 232 Methods I
  • BIST 233 Methods II
  • BIO 227 Fundamental Concepts in Gene Mapping or BIO 257 Computational and Statistical Methods in Human Genetics
  • BIST 298 Introduction to Computational Biology and Bioinformatics
  • EPI 201 Introduction to Epidemiology: Methods I (or equivalent)
  • EPI 507 Genetic Epidemiology

Recommended Elective Courses:

  • BIST 235 Advanced Regression and Statistical Learning Methods
  • BIST 244 Analysis of Failure Time Data
  • BIST 245 Multivariate and Longitudinal Data Analysis
  • BIST 249 Bayesian Methods in Biostatistics or STAT 220 Bayesian Data Analysis
  • BIST 250 Probability Theory and Applications II
  • BIST 251 Statistical Inference II

Computational Biology and Bioinformatics
  • BIST 299 Advanced Computational Biology and Bioinformatics
  • HST 508 / Biophysics 170 Quantitative Genomics and Evolution
  • Biophysics 205 Computational and Functional Genomics

Data Structures and Programming
  • BIO 510 Programming I
  • BIO 511 Programming II
  • BIO 514 Introduction to Data Structures and Algorithms

Epidemiology and Genetic Epidemiology
  • EPI 207 Advanced Epidemiologic Methods
  • EPI 222 Genetic Epidemiology of Diabetes and its Complications
  • EPI 244 Genetic Epidemiology of Psychiatric Disorders
  • EPI 289 Models for Causal Inference
  • EPI 293 Analysis of Genetic Association Studies Using Unrelated Subjects
  • EPI 511 Advanced Population and Medical Genetics
  • ID 542 Methods for Mediation and Interaction
  • EH 298 Environmental Epigenetics
  • EH 516 Environmental Genetics
  • IMI 231 Introduction to Computational Genomics for Infectious Disease

Molecular Biology, Physiology, and Genetics
  • EPI 249 Molecular Biology for Epidemiologists
  • BPH/EH 205 Human Physiology
  • BPH/EH 208 Pathophysiology of Human Disease
  • GEN 201 Principles of Genetics
  • BCMP 200 Molecular Biology
  • MICRO 200 Molecular Microbiology and Pathogenesis

The following courses might be useful for students to prepare for taking the above genetic and genomic courses:
  • BIO 509 Introduction to Statistical Computing Environments
  • BIO 290 Introductory Genomics and Bioinformatics for Health Research
  • Biophysics 101 Computational Biology
The following courses can be counted towards 35 credit Biostatistics Electives: BIO 235, 244, 245, 247, 249, 250, 251, 298, 299, 514.