John Quackenbush, PhD
Professor of Cancer Biology, Dana-Farber Cancer Institute
Professor of Biostatistics and Computational Biology, Dana-Farber Cancer Institute
Director of the Center for Cancer Computational Biology at Dana-Farber Cancer Institute
Office phone: 617-582-8163
Website: Functional Genomics and Computational Biology
Preferred contact method: email
Area of Research
Computational Biology and Functional Genomics
Dana-Farber Cancer Institute
450 Brookline Avenue
Boston, MA 02215
John Quackenbush earned his PhD in theoretical particle physics from UCLA in 1990 and then completed a postdoctoral fellowship in experimental high energy physics. After receiving a fellowship from the National Center for Human Genome Research, he worked with Glen Evans on the physical mapping of human chromosome 11, and later with Richard Myers and David Cox on large-scale DNA sequencing of chromosomes 21 and 4. In 1998 he joined the faculty at The Institute for Genomic Research (TIGR) where his work focused on the use of genomic and computational methods for the study of human disease. He joined DFCI in 2005 where his work has increasingly focused on the analysis of women's cancers and pulmonary disease, although the methods he and his group develop can be broadly applied. In 2009 he launched the Center for Cancer Computational Biology (CCCB), a Dana-Farber Strategic Plan Center that provides computational support and access to genomic analysis more broadly to the DFCI research community.
ResearchComputational Biology and Functional Genomics
Every revolution in science has been driven by one thing: data. From the Copernican Revolution to the evolution of quantum mechanics to uncovering the structure and function of DNA, data has enabled us to expand our understanding of the universe and ourselves. The first human genome sequence—its ordered collection of chemical letters—was completed in 2000, allowing us to identify a parts list consisting of the more than 25,000 proteins that make up our cells. Today, new technologies are allowing us to sequence individual genomes for a few thousand dollars and in a matter of days, opening up unprecedented opportunities to discover the associations between the genes encoded in the genome and their manifestations in the physical phenotypes we observe, including their associations with disease.
My research focuses on integrating multiple sources of information—genomic data, clinical information, knowledge gleaned from the published scientific literature—to begin to map out the networks that drive processes within cells and to understand how the networks change as diseases like cancer develop and progress. Our hope is that by fully understanding those networks, we can develop strategies to better treat disease and to minimize the impact of therapy on normal, healthy cells.
Our commitment is to build on what we learn to develop software and tools that will stimulate and facilitate research at DFCI which will be made widely and freely to the broader research community.
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