Bioinformatics master of science degree

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Explore the unique combination of biotechnology, programming, and computational mathematics to combat illness and create novel technologies for industry.

The bioinformatics masters combine biotechnology, computer programming, and computational mathematics to prepare you to utilize and create technologies that will discover, treat, and cure a range of medical illnesses.

The MS degree in bioinformatics provides students with a strong foundation in biotechnology, computer programming, computational mathematics, statistics, and database management. Graduates are well-prepared for academia and careers in the biotechnology, bioinformatics, pharmaceutical, and vaccine industries.

Based on consultation with individuals within the industry nationwide, the job market is rich with opportunities for those who obtain a graduate degree in bioinformatics, particularly when coupled with research as thesis work. This research provides exposure to real-world problems—and their solutions—not otherwise attainable in an academic setting.

The program provides you with the capability to enter the bioinformatics workforce and become leaders in the field. The curriculum is designed to fulfill the needs of students with diverse educational and professional backgrounds. Individuals entering the program typically have degrees in biology, biotechnology, chemistry, statistics, computer science, information technology, or a related field. The program accommodates this diversity by providing a comprehensive bridge program for students who need to supplement their education before entering the program. The program offers two tracks, one for students with backgrounds in the life sciences and one for those with backgrounds in the computational sciences. Regardless of the track pursued, students are prepared to become professional bioinformaticists upon graduation.

The program is offered on a full- or part-time basis to fulfill the needs of traditional students and those currently employed in the field.

Plan of study

A minimum of 30 semester credit hours is required to complete the program. A number of graduate electives are offered for students to pursue areas of personal or professional interest. In addition, every student is required to complete a research project that addresses a relevant and timely topic in bioinformatics, culminating in a thesis. Graduate electives may be chosen from relevant RIT graduate courses.


  • Biotech and Life Sciences

  • Medical Devices

  • Pharmaceuticals

  • Health Care

Typical Job Titles

Senior Analyst/Programmer Associate Systems Analyst
Bioinformaticist Bioinformatics Analyst
Bioinformatics Engineer Developer
Computational Biologist Research Technician
Software Engineer


Bioinformatics, MS degree, typical course sequence

Course Sem. Cr. Hrs.
First Year
Bioinformatics Seminar
The course provides opportunities for students and faculty to develop and share professional interests while discussing current trends and developments in bioinformatics. Material for this course will be drawn from the current scientific literature.
Graduate Bioinformatics Algorithms
Bioinformatics Algorithms will focus on the types of analyses, tools, and databases that are available and commonly used in Bioinformatics. The labs will apply the lecture material in the analysis of real data through computer programming.
Graduate Ethics in Bioinformatics
This course will be focused on individual and organizational responsibilities in bioinformatics research, product development, product commercialization and clinical and consumer genetic testing.
Database Management for the Sciences
Students will learn to create and maintain efficient relational databases for use in modeling and analysis in the sciences. Topics will include an introduction to relational algebra, SQL, and advanced relational designs.
This course is an introduction to the probabilistic models and statistical techniques used in the analysis of biological and medical data. Topics include univariate and multivariate summary techniques, one and two sample parametric and nonparametric inference, censoring, one and two way analysis of variance, and multiple and logistic regression analysis.
Graduate Molecular Modeling and Proteomics
This course will explore two facets of protein molecules: their separation and their structure. The structure component will build upon information from earlier bioinformatics courses. Protein separation techniques will be addressed in lectures with descriptions of 2D gel electrophoresis and chromatography. Algorithms of protein secondary structure prediction will be implemented. Experimental techniques for tertiary structure determination such as NMR will be covered. The course will also include the analysis of inter-molecular interactions, such as ligand/receptor pairing, by employing software that permits modeling of molecular docking experiments.
Graduate Elective*
Second Year
Masters-level research by the candidate on an appropriate topic as arranged between the candidate and the research advisor.
Total Semester Credit Hours

Admission Requirements

To be considered for admission to the MS program in bioinformatics, candidates must fulfill the following requirements:

  • Complete a graduate application.
  • Hold a baccalaureate degree (or equivalent) from an accredited university or college in biology, biotechnology, biochemistry, chemistry, computer science, information technology, statistics, or a related discipline.
  • Submit official transcripts (in English) of all previously completed undergraduate and graduate course work.
  • Have a minimum cumulative GPA of 3.2 (or equivalent)
  • Submit two letters of recommendation from academic or professional sources.
  • International applicants whose native language is not English must submit scores from the TOEFL, IELTS, or PTE. A minimum TOEFL score of 79 (internet-based) is required. A minimum IELTS score of 6.5 is required. The English language test score requirement is waived for native speakers of English or for those submitting transcripts from degrees earned at American institutions.

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