Master of Science – Computational Biology and Quantitative Genetics

About

The Master of Science in Computational Biology and Quantitative Genetics is designed to provide you with the statistical skills required to appropriately analyze large quantitative datasets as well as the epidemiological skills necessary to design, conduct, and evaluate experiments. 

You will receive training in quantitative methods, including linear and logistic regression, survival analysis, longitudinal data analysis, statistical computing, clinical trials, statistical consultation and collaboration, and epidemiology. You will also gain a strong foundation in modern molecular biology and genetics, computer programming, the use and application of tools for analysis of genomic data, methods for integrative analysis, and meta-analysis of genes and gene function. 

The program is intended as a terminal professional degree that enables you to launch your career in bioinformatics. It can also provide the foundation for further doctoral studies in biostatistics, epidemiology, computational biology, and other related fields. 

On Campus (Fall start) • Full-time (2 years)

Curriculum

Competencies

• Interpret the results of analyzing diverse types of biological data by applying basic understanding of molecular genetics, the structure and organization of the human genome, gene expression regulation, epigenetic regulation, gene functional descriptions, and modern technologies including genotyping, genome-seq, exome-seq, RNA-seq, ChIP-seq, etc., and their applications, and as well understanding of metagenomics.
• Use the major genomics data resources, develop basic knowledge of sequence analysis, gain familiarity with gene functional annfunctional annotation and pathway analysis, the ability to write data management and analysis scripts, working knowledge of data mining and statistical analysis techniques as well as machine learning approaches, and understanding of modern network modeling techniques.
• Understand how to use UNIX commands, a scripting language such as perl or python, an advanced pro-gramming language such as C, C++, or Java, and R/Bioconductor, and familiaritywith database programming and modern web technologies to interrogate biological data and to interpret the results of any analysis.
• Use basic statistical inference and applied regression, survival, longitudinal, and Bayesian statistical analysis in the analysis of biological data to identify statistically significant features that correlate with phenotype.
• Critically evaluate and apply principles of epidemiologic methods, including exposure and outcome measures, measures of association, bias and confounding, and study design options.

Our Community

The Master of Science in Computational Biology and Quantitative Genetics, part of the Department of Biostatistics, offers a wide range of resources including networking opportunities, career services, and the chance to conduct research with the Harvard Chan School’s faculty and staff. The program has also collected resources to help students improve their technical skills in coding and statistics.  

Harvard Chan School offers a wide variety of academic support services, including research support through the Countway Library of Medicine and academic coaching and tutoring for students seeking additional help with either an overall transition to graduate school or specific subject matter.  

Beyond academics, the school is home to more than 40 official student organizations focusing on public health issues, cultural affinities, and extra-curricular interests. These groups and other offices throughout the school plan events on campus and around Boston.  

Career Outcomes

The Master of Science (SM-80) CBQG graduates have found employment as bioinformatics analysts or engineers in the following industries:  

• Universities 
• Hospitals 
• Research Organizations 
• Pharmaceuticals 
• Biotechnology 

Eligibility Criteria

• An undergraduate degree in mathematical sciences or allied fields (e.g. biology, psychology, economics)
• 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
• At least one semester of training in biology, with some familiarity with molecular biology and genetics

Application Requirements

All applications must be submitted through SOPHAS – the centralized application service for public health programs. In addition to the application, applicants must submit:

• Statement of purpose and objectives
• Official test scores
• Three letters of reference
• Resumé/curriculum vitae
• Post-secondary transcripts or mark sheets (World Education Services credential evaluation for applicants with degrees from outside of the United States.)
• English language proficiency (TOEFL/IELTS/Duolingo English Test), if applicable

Application Deadline: December 1

Applicants may apply to only one degree program for either full- or part-time status. Applications are reviewed in their entirety and decisions are released via email in late February/early March. Decisions are not released until all application components are received.

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