Computational Biology and Bioinformatics Track

Computational methods and expertise have become essential to modern biological research.  In the past two decades, numerous discoveries and breakthroughs have relied on the development of innovative bioinformatics tools and integrative data analysis, such as the completion of the human genome, identification and annotation of genes and proteins, modeling and prediction of protein structures and functions, single cell and spatial genomics, etc.  The computational and bioinformatics (CBB) track in DGP, led by Dr. Feng Yue, reflects a growing need for training in this rapidly expanding area.  It provides students with a significant strategic advantage post-graduation by equipping them with the interdisciplinary skills necessary to address the increasingly data-intensive nature of modern biomedical research. Through a structured combination of coursework, hands-on training, and collaborative engagement, the track integrates computational methods, biological inquiry, and machine learning approaches—preparing trainees to work at the forefront of discovery and translational science.

Curriculum

Required courses:

DGP 402 Fundamentals of Biomedical Sciences 1 (All DGP Students) (1 credit)

DGP 404 Fundamentals of Biomedical Sciences 2 (All DGP Students) (1 credit)

DGP 494 Colloquium on Integrity in Biomedical Research (All DGP Students) (0 credits)

DGP 496 Introduction to Life Sciences (All DGP Students) (1 credit)

DGP 485, Data Science for Biomedical Researchers (1 credit)

DGP 486, Advanced Bioinformatics (1 credit)

Electives

One graduate-level biostatistics course; Two graduate level bioinformatics or computer science courses. The final elective may be a DGP-approved computational or biology course of the student’s choosing.

Mentor Selection

The mentor or co-mentor should be a core faculty member in the CBB track.  

 All academic milestones, qualifying exam, and graduation requirements are the same as all other DGP students.

Applicants

The CBB track is an advanced curriculum. Successful applicants will have strong computer science, computational, bioinformatic or mathematics backgrounds. Applicants should select DGP (program code L20PH) as the program and the application form will ask if you are interested in applying for the Computational Biology and Bioinformatics Track.