Master’s Program

Prospective students who have completed a bachelor’s degree may apply for direct admission to the Master of Science (MS) program for either full-time or part-time admission. The master’s degree requires a total of 32 credits.

BU Bioinformatics Program Merit Scholarships

Tuition assistance is available to master’s students in the form of Merit Scholarships, which provide partial tuition to full-time MS students.  These scholarships are awarded at the time of admission and do not require a separate application. These awards are made to both international students and U.S. citizens who have demonstrated excellent academic ability and who have demonstrated enthusiasm and knowledge in the field of Bioinformatics.

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The degree requires the completion of 32 credits including the core courses listed below. Students must also demonstrate a working knowledge of computational methods available to the modern bioinformatician by having an internship as part of their degree requirements. Upon completion of the internship, the student is required to submit a written and oral report on the internship experience. This report serves in lieu of an MS thesis.

Core Courses

MS students are expected to fulfill all of the core course requirements listed below, and must demonstrate mastery of the core subject matter (no lower than a “B” in each core course is acceptable). Fulfillment of core course equivalents will be determined based on documented previous academic and/or work experience. When either past work or an alternate course has been accepted as a core equivalent, the student’s advisor will recommend other courses to fulfill the requirements.

ENG BE 562: Computational Biology: Genomes, Networks, Evolution

The algorithmic and machine learning foundations of computational biology, combining theory with practice are covered. Principles of algorithm design and core methods in computational biology, and an introduction of important problems in computational biology. Hands-on experience analyzing large-scale biological data sets. 4 cr.


ENG BF 528: Applications in Translational Bioinformatics

The objective of this course is expose students to the topics and technologies used in modern bioinformatics studies. The course covers a mix of biological and computational topics, including: high throughput genomics techniques, current high throughput sequencing assays, differential gene expression techniques, phylogenetic techniques, microbiome/metagenomics techniques, metabolomics, proteomics, systems, network, and integrative biology, basic linux cluster usage, python and R scripting.  This is a ‘flipped’ course, where the traditional lecture materials are made available online and in-class periods are dedicated to concerted group work and interactive discussions. The course materials are focused on real-world applications of the high throughput genomics techniques and organized into structured group projects. 4 cr.

ENG BE 768: Biological Database Systems

Describes relational data models and database management systems; teaches the theories and techniques of constructing relational databases to store various biological data, including sequences, structures, genetic linkages and maps, and signal pathways. Introduces relational database query language SQL and the ORACLE database management system, with an emphasis on answering biologically important questions. Summarizes currently existing biological databases. Describes web-based programming tools to make databases accessible. Addresses questions in data integration and security. The future directions for biological database development are also discussed. 4 cr.

ENG BF 571: Dynamics and Evolution of Biological Networks

This course focuses on mathematical models for exploring the organization, dynamics, and evolution of biochemical and genetic networks. Topics include: introductions to metabolic and genetic networks, deterministic and stochastic kinetics of biochemical pathways; genome-scale models of metabolic reaction fluxes; models of regulatory networks; modular architecture of biological networks. 4 cr.

ENG BF 831: Translational Bioinformatics Seminar

This course enrolls students who intend to pursue careers in medicine, dental medicine and/or medical research (either academic or industrial). 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. 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 intervention (e.g. prognostic, diagnostic or therapeutic). Brief guest presentations by researchers in BUSM laboratories will be arranged as
appropriate. Previous guest facilitators have included faculty from the Department of Biostatistics, Section of Computational Biomedicine, and Department of Mathematics and Statistics as well as industry leaders. 2 cr.

CAS BI 552: Molecular Biology I

Synthesis, structure, and function of biologically important macromolecules (DNA, RNA, and proteins). Regulation and control of the synthesis of RNA and proteins. Introduction to molecular biology of eukaryotes. Discussion of molecular biological techniques, including genetics and recombinant DNA techniques. 4 cr.


The remaining credits need for the MS include elective courses in such areas as: Bioinformatics, Mathematics, Computer Science, Chemistry, Biostatistics, Biomedical Engineering, Biology, Molecular Biology, Cell Biology and Biochemistry, Electrical and Computer Engineering.

Master’s Program with a Concentration in Translational Medicine

The goal of this program is to train physician-scientists who will be leaders in applying and stimulating the development of post-genomic technologies to clinical research and the practice of medicine. The master’s degree requires a total of 32 credits. MS candidates must demonstrate mastery of the core subject matter (no lower than a “B” in core courses) and complete a master’s research project with a written and oral report which will serve as a master’s thesis. Candidates will be expected to develop their ideas to the point of publication. Click here for more information, including curriculum information.