Master’s in Bioinformatics

The field of bioinformatics involves managing and analyzing large biological datasets to better understand complex living systems and improve human health. Key bioinformatics tasks include analyzing genomic sequences and structures, studying evolutionary relationships, interpreting omics experiments, and analyzing gene networks. This course introduces graduate students to foundational problems in bioinformatics and provides hands-on experience with the databases and computational tools used to address these challenges.

The course emphasizes practical skill development in computer labs, enabling students to apply bioinformatics methods in their research. Familiarity with basic molecular biology is recommended. While prior programming knowledge is beneficial, it is not required. Enrollment is currently limited to master’s students in the Bioinformatics Program.

Describes relational data models and database management systems. Teaches the theories and techniques of constructing relational databases with emphasis on those aspects needed for various biological data, including sequences, structures, genetic linkages and maps, and signal pathways. Introduces relational database query language SQL. Summarizes currently existing biological databases and the Web-based programming tools for their access. Object-oriented modeling is introduced primarily as a design aid for dealing with the particular complexities of biological information in standard RDB design. Emphasis will be on those problems associated with dealing with data whose nomenclature and interrelationships are undergoing rapid change.

This course enrolls students who intend to pursue careers in medicine, dental medicine, and/or medical research (either academic or industrial)—in particular, students in the BF for Translational Medicine track of the Bioinformatics MS program. After commencing briefly with general introductory material (published reviews and other relevant back-ground information), students will proceed to examine, discuss, and evaluate recent papers that directly illustrate the use of bioinformatics either in pre-clinical or clinical research settings. Papers will be drawn from high-impact journals such as Nature, Science, PNAS, Cell, and Science Translational Medicine. Students will take turns presenting the papers to the class and provide a critical review of each, both orally and in writing. They will also complete a term paper in the form of a research proposal directed to the goal of using bioinformatics to advance a medical procedure—either diagnostic or therapeutic. Brief guest presentations by researchers in BUSM laboratories will be arranged as appropriate.

Internships provide the bridge between classroom/laboratory study and real- world employment. Each student must complete an internship with a minimum of 400 hours of on-the-job experience (e.g., 10 weeks full-time work in the summer). The format is very flexible, and part-time internships running concurrently with classes or employment are acceptable.

At the conclusion of the internship the student must submit a report that summarizes (a) the project they worked on (in general terms), (b) work accomplished (with very specific emphasis on the student’s contribution), and (c) description of the impact of the experience on the student’s professional development. Reports need not be more than two double-spaced text pages in length, though longer reports are acceptable. Append any detailed material that supports the narrative (tables, figures, publications, progress reports, etc.). In cases where confidentiality agreements restrict release of pertinent project details, the report can describe the work in terms sufficiently general as to be acceptable to the company in which the work was done.

• R for Biological Sciences
• Special Topics: Learning From Large-Scale Biological Data
• Data Science Tools and Applications
• Machine Learning
• Data Science in R
• Introduction to Statistical Applications in R
• Statistical Methods and Applications for Genomics
• Data Science and Statistical Modeling in R
• Bayesian Modeling for Biomedical Research and Public Health
• Applied Genetic Analysis
• Biomolecular Architecture
• Advanced Topics in BME: Methods and Logic in Quantitative Biology
• Molecular Biology II (CM)
• Drug Discovery in Neuroscience
• Developmental Biology
• Microbiome: Our Intimate Relationship with Microorganisms
• Advanced Cell Biology
• Physical Biochemistry
• Advanced Topics in Chemical Physics
• Numerical Analysis I
• Linear Models
• Generalized Linear Models
• Probability
• Mathematical Statistics
• Introduction to Stochastic Processes
• Modern Regression Analysis in R
• Discrete Stochastic Models
• Principles of Genetics and Genomics
• Introduction to Pathology and Pathophysiology of Disease
• Molecular Biology Laboratory

A. Our program features a crucial built-in internship experience where you embed directly into a professional setting. You will gain hands-on experience at a local Boston institution—one of the world's largest biotech hubs! This internship is part of your program curriculum.

A. You will master the most relevant, in-demand skills, including Biological Data Analysis at Scale, Genomics, and Integrated Computational Thinking.

A. We ensure the curriculum remains cutting-edge by actively incorporating AI methods and novel computational techniques taught by leaders in the field. You learn to build tools that are so effective, they are used by thousands of researchers globally.

A. Graduates from the program are successful at getting jobs in academia and industry. The field is in high demand, and our expansive alumni network at companies like Pfizer, Genentech, and Mass General Hospital create immediate connections. Your work will directly apply to what employers are looking for today.

A. Yes, the program is highly multidisciplinary, seeking students from various backgrounds, including biology, computer science, and statistics. We are looking for candidates who are prepared to transition from a technical role to an innovative, creative leader—someone with a passion for driving the next generation of biological discovery.

A. All full-time Master’s in Bioinformatics students who request financial aid receive some level of tuition assistance. Merit scholarships provide partial tuition and are awarded at admission without a separate application. They are available to both international students and US citizens who demonstrate excellent academic ability, enthusiasm, and knowledge in the field. Learn more about financial aid for Master’s Students.