Welcome
Our main research interest is in understanding the structure and function of genomes, especially those of medical or
agricultural importance. The core strength of our research is in developing novel algorithms and computational systems
for large-scale biological sequence analysis, including leading algorithms for de novo genome assembly, variant detection,
and related –omics assays. Using these advances we have contributed to the de novo genome assemblies of dozens of species;
probed the sequence variations related to autism, cancer, and other human diseases; mapped the transcriptional and epigenetic
profiles of tomatoes, corn, and other important plant species; and explored the role of microbes in different environments.
In response to the deluge of biological sequence data we are now facing, we have also been at the forefront of distributed
and parallel computing in genomics, and have pioneered the use of cloud computing as an enabling platform to
address the big data challenges we are all facing.
Looking forward, we see ourselves at the intersection of biotechnology and algorithmics, developing systems for probing
the structure and function of genomes using the best technologies possible. Our expertise spans from low level computer
architecture, through sequencing, de novo assembly, variant identification, transcriptome & other -omics data
and up to machine learning approaches to build predictive models of diseases and treatment response. In addition to ongoing
projects in autism, cancer, and other human diseases, we also study agricultrual systems to better understand the underlying
genotype to phenotype relations. Altogether, we intend to develop powerful new methods for analyzing large collections
of genomes to address questions of disease, development, and evolution. Among other recognition, for this work I was granted
an NSF CAREER award, a Sloan Foundation Fellowship, and was named a TIME100 recipient in 2022.
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Michael Schatz
Bloomberg Distinguished
Professor of Computer Science
and Biology
CS office and Mailing address:
Johns Hopkins University
Department of Computer Science
3400 N Charles St
Malone Hall 323
Baltimore, MD 21218
Department of Biology:
UTL 391 (office)
UTL 398 (lab and conference room)
Cell: (703) 966-1987
E-mail: mschatz <at> cs.jhu.edu
Twitter: @mike_schatz
LinkedIn: mschatz
BlueSky: mikeschatz.bsky.social
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