Bioinformatics, Computational & Systems Biology, and Biomedical Informatics

The broad area of Bioinformatics applies computer science techniques to analyze and interpret biological data.  At Tufts, bioinformatics research and education span several key topics including computational biology, systems biology, bioengineering, and biomedical informatics. Key underlying techniques are machine learning and AI, statistical science, and algorithms.

Professors Donna Slonim and Lenore Cowen lead the Tufts Bioinformatics and Computational Biology (BCB) research group.  The group is focused on the application of computational, mathematical, and statistical methods to the solution of practical biomedical problems.  The group also has an interest in understanding and characterizing biological networks. In addition, Professor Slonim's research interests include translational medicine, clinical pharmacogenomics and transcriptomics, while Professor Cowen has a longstanding interest in structural approaches to protein function prediction. See

Led by Professor Soha Hassoun, the mission of the Hassoun Lab, is to develop ANALYSIS + DESIGN tools to advance (re-)designing biology. These tools provide insight into complex biological systems. The tools also enable building novel biological components to produce useful chemicals and therapeutics.  Professor Hassoun has ongoing projects for pathway and modularity analysis of biochemical networks, creating extended metabolic models based on enzyme promiscuity, and developing tools for analyzing metabolomics. Professor Hassoun closely collaborates with Professors Mike Hughes and Li-Ping Liu on the machine learning aspects of the research and with Professors Nikhil U. Nair and Kyongbum Lee from Tufts Department of Chemical and Biological Engineering on the biological engineering aspects of her research. She also has collaborators in the School of Medicine and the Cummings School of Veterinary Medicine at Tufts. See

Professor Mike Hughes's research group is focused on machine learning applications to clinical medicine. Active projects include helping clinicians understand and treat diseases like depression and infertility by training probabilistic models to make personalized drug recommendations for new patients based on the thousands of electronic health records observed from previous patients.

Based in the Department of Computer Science, with ties to the School of Engineering, the School of Medicine, Tufts Medical Center, the Cummings School of Veterinary Medicine, the Friedman School of Nutrition Science and Policy, and the School of Arts and Sciences, the university is a great place for Ph.D., Masters, and undergraduate research programs in Bioinformatics and other related topics.

We welcome graduate and undergraduate students. Reach out to one of our faculty to discuss a research topic. We also welcome visitors: come meet us, attend or speak at one of our group meetings.