Bioinformatics

Study mode:On campus Study type:Full-time Languages: English
Local:$ 49.9 k / Year(s) Foreign:$ 49.9 k / Year(s) Deadline: Jan 15, 2026
155 place StudyQA ranking:2651 Duration:2 years

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The Bioinformatics program at Tufts University offers students an interdisciplinary education at the intersection of biology, computer science, mathematics, and data analysis. Designed to prepare students for the rapidly evolving field of biological data analysis, the program emphasizes the development of skills necessary to interpret complex biological data sets, including genomic sequences, proteomics, transcriptomics, and systems biology data. With a curriculum that integrates theoretical foundations and practical applications, students gain expertise in computational methods, statistical techniques, and informatics tools essential for modern biological research and biomedical innovation.

Throughout the program, students engage in coursework covering molecular biology, genetics, algorithms, programming languages such as Python and R, data visualization, and machine learning. Hands-on laboratory experiences and research projects allow students to apply their skills to real-world problems, such as genome annotation, personalized medicine, drug discovery, and evolutionary biology. The faculty are distinguished researchers and industry professionals who provide mentorship and collaborate on cutting-edge projects, ensuring that students are well-prepared for careers in academia, biotechnology, pharmaceuticals, healthcare, and data science.

The program also emphasizes ethical considerations, data privacy, and the societal impacts of bioinformatics, fostering responsible and informed practitioners. Tufts’ state-of-the-art facilities and strong connections with major research institutions and biotech industries offer invaluable networking and internship opportunities. Graduates of the Bioinformatics program are equipped to contribute to scientific advancements, develop innovative computational tools, and address global health challenges through data-driven approaches. Whether pursuing careers in research, healthcare, or industry, students will find a comprehensive and dynamic educational experience that equips them with the knowledge and skills to excel in the growing field of bioinformatics.

This program assumes some undergraduate-level experience in Computer Science (or comparable industry expertise programming in C, C++, or Java) and fundamental knowledge of biology and chemistry.

Year 1
Fall Spring
BioE 291 - Bioengineering Seminar Bio E292 - Bioengineering Seminar
†Comp 135 - Machine Learning BME 162 - Molecular Biotechnology
EE 104 - Probability *Comp 167 - Introduction to Computational Biology
Year 2
Fall Spring
‡ChBE 167 - Metabolic and Cell Engineering †Comp 160 - Algorithms
†Systems elective: Comp 111 (Operating Systems) or Comp 112 (Networks) or Comp 115 (Database Systems) or a similar course. †Comp elective: an advanced Comp course in bioinformatics, algorithms, machine learning, or another related topic (recent options include Biological Networks and Systems, Scientific Visualization, Stochastic Search and Genetic Algorithms, Advanced Algorithms, etc.)
†Comp 293/295 - Graduate Research/MS Thesis  

*Track requirement
†Track elective
‡Breadth elective (fulfills core requirement)

 

  • Application for admission
  • Scanned copies of all college transcripts
  • (3) Letters of Recommendation
  • Résumé
  • Personal statement
  • Application fee of $85 (non-refundable)
  • GRE General Test scores required.

Scholarships

For students who show scholarly promise, the Graduate School of Arts and Sciences and the School of Engineering offer scholarships, fellowships, and research or teaching assistantships to full-time students in doctoral programs. The Graduate School of Arts and Sciences also offers awards to full-time students in master’s programs. Certificate students are not eligible for these awards.

  • Tuition Scholarships are available in most master's and doctoral programs for qualified students.
  • Teaching Assistantships are offered by most departments.
  • Research Assistantships are generally available in the science and engineering areas.
  • Fellowships are offered to students who demonstrate outstanding records of achievement and a well-articulated plan of study.

The Bioinformatics program at Tufts University offers students a comprehensive education in the interdisciplinary field that combines biology, computer science, and mathematics. Designed to prepare graduates for careers in research, healthcare, and biotechnology industries, the program emphasizes the development of skills necessary to analyze and interpret complex biological data. Students gain expertise in computational methods, statistical analysis, and biological research techniques, enabling them to contribute to advancements in genomics, proteomics, systems biology, and personalized medicine. The curriculum includes coursework in molecular biology, algorithms, data structures, statistical modeling, and programming languages such as R and Python. In addition to coursework, students have opportunities for research projects, internships, and collaborations with faculty involved in cutting-edge bioinformatics research. The program aims to equip students with both theoretical knowledge and practical skills, fostering the ability to design and implement computational solutions to biological problems. Graduates of the program are well-positioned to pursue careers in academia, industry, or further study in graduate or medical schools. The university's state-of-the-art laboratories and research centers provide an ideal environment for experiential learning and innovation. Tufts also encourages interdisciplinary collaboration, allowing students to engage with programs in medicine, engineering, and computer science. The Bioinformatics program’s faculty are leaders in their fields, providing mentorship and guidance to support student success. Overall, Tufts University’s Bioinformatics program prepares students to become proficient computational biologists capable of making meaningful contributions to science and healthcare through the analysis of biological data.

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