Felix Dietlein

Felix Dietlein

Assistant Professor of Pediatrics
Felix Dietlein

Dr. Dietlein is an Assistant Professor at Harvard Medical School, an Associate Member of the Broad Institute, Core Faculty in the Computational Health Informatics Program at Boston Children’s Hospital, and an Investigator at the Dana-Farber Cancer Institute (www.dietleinlab.org). His research focuses on data-driven precision cancer medicine – to decode the genomic principles of tumor development, overcome barriers to discovering actionable lesions in cancer genomes, maximize the potential of sequencing technologies in patient care, and innovate genome-inspired diagnostics and cancer therapies.  

Toward these goals, his lab developed the first algorithm for discovering noncoding drivers in cancer genomes (Science 2022), created a comprehensive resource of coding drivers in 11,873 patients (Nature Genetics 2020), and established a platform for designing driver-directed combination therapies (Cell 2015). He is also interested in translating genomic discoveries into new driver-directed treatments (Cancer Discovery 2014; PNAS 2012).  

Dr. Dietlein firmly believes that the future of cancer medicine depends on our ability to decode the genomes of millions of patients and turn them into powerful weapons against cancer. His mission is to bring scientists from different disciplines together and train the next generation of exceptional scientists in his lab. With the start of each trainee, he tailors a training plan to their specific strengths and needs, develops actionable teaching goals, and identifies potential co-mentors and required resources. His teaching also includes weekly meetings, peer mentorship, and a joint weekly seminar series. The multidisciplinary research program of his lab allows computational trainees to immediately experience the translational potential of their work on the future of precision cancer medicine.

Contact Information

Boston Children's Hospital
401 Park Drive, Landmark Center Bldg, LM 5528.6
Boston, MA 02215
p: 617-306-9754

AIM or BIG Faculty

Primary affiliation

Methodological Focus