Frequently Asked Questions

Q.

How do the 80-credit masters programs in Biostatistics and Epidemiology, the 60-credit masters program in Health Data Science (HDS), and the 80-credit masters program in Computational Biology & Quantitative Genetics (CBQG) differ from each other?

A.

All four programs are complementary and each is designed to provide students with a great degree of flexibility in choosing courses to develop specific competencies. The SM2-CBQG program has a strong focus on the analysis and interpretation of complex genomic data; research is normally motivated by the need to solve a biological problem using computational methods, and students will learn about genomic databases, micro array analysis, next generation sequencing, human genetics, and laboratory techniques. The SM60-HDS program is focused more on computational methods, software engineering, and data wrangling; research is motivated by the need to make sense of health-related data, such as electronic medical records, cell phone data, and environmental exposures – in other words, data that is not necessarily genomic. Working with their advisor, students design an individual program, drawing upon a broad and often overlapping selection of required and elective courses.

One key difference is that the new SM2 in Computational Biology and Quantitative Genetics requires a 10-20 credit Collaborative Research Thesis experience. The focus here is on giving students practical experience that is likely to be of interest to potential employers.

Strengths and weaknesses of the undergraduate record, work experience, career goals, and future educational plans will normally inform an applicant’s choice in selecting the degree program that is right for them. And as a student’s interests evolve, in some cases he or she may petition to transfer between programs in their second year.

Q.

Explain the specific differences between:

  • The SM2 in Computational Biology and Quantitative Genetics
  • The SM in Health Data Science
  • The SM2 in Epidemiology with a Specialization in Genetic Epidemiology and Statistical Genetics

A.

Again, there is a good deal of potential overlap between these programs, so specific interests and future plans will guide the student to a particular program. The following table summarizes degree requirements for the three programs.

Entrance Requirements Required Coursework Thesis
SM2 in Computational Biology and Quantitative Genetics
  • Bachelor’s degree in the mathematical sciences or allied fields (biology, psychology, economics, etc.).
  • Successful completion of calculus through partial differentiation and multivariable integration
  • One semester of linear algebra or matrix methods
  • Either a two-semester sequence in probability and statistics or a two-semester sequence in applied statistics
  • Applicants should have at least one semester of training in biology, with some familiarity with molecular biology and genetics
  • Practical knowledge of computer scripting and programming as well as experience with a statistical computing package such as R are highly desirable
  • Applicants are encouraged to have completed other courses in quantitative areas and in areas of application in the biological sciences
  • Additional research or work experience is considered beneficial, but not required.
55 credits total

  • 15-22.5 credits in biostatistics, depending on track selected
  • 5-12.5 credits in epidemiology, depending on track selected
  • 20-35 credits in elective courses
10-20 credit Collaborative Research Thesis
SM in Health Data Science
  • An undergraduate degree in mathematical sciences or allied fields (e.g. statistics, computational biology, mathematics, economics, statistics, computer science, physics, or engineering)
  • Calculus through partial differentiation and multivariable integration
  • One semester of linear algebra or matrix methods
  • Either a two-semester sequence in probability and statistics or a two-semester sequence in applied statistics
60 credits total

  • 25 credits in data science core curriculum
  • 5 credits in computer science
  • 22.5 credits in elective courses
7.5 credit
Project-Based Research Course
SM2 in Epidemiology Specialization in Genetic Epidemiology and Statistical Genetics
  • Bachelor’s degree
  • Strong background in relevant disciplines (e.g., biology, chemistry, genetics, physiology, bioengineering, and related social and computational sciences) and mathematics
  • Excellent quantitative GRE scores
  • Clear research goals
75 credits total

  • 30 required credits in Epidemiology
  • 15 required credits in Biostatistics
  • 30 credits in elective courses
5 credit thesis required