Daniel Skelly, Ph.D.
Senior Computational Scientist
Biologist and data scientist harnessing single cell functional genomics and genetically diverse mice to study complex traits
Variation in observable traits, such as disease susceptibility, is pervasive in the natural world. Recent advances in sequencing and computation are providing us with an unprecedented view of patterns of genetic variation within species. A major outstanding challenge is to identify and characterize the specific genetic variants affecting complex traits, and the mechanisms through which they do so.
I am a biologist and data scientist who uses single cell functional genomics to understand the genetic basis of complex traits. I utilize genetically diverse model organism populations together with the methodology of statistical and quantitative genetics to reveal novel mechanistic insights into the biology of complex traits. My background and interests include cancer, cardiovascular disease, diabetes, and obesity/metabolic disorders.
Education and experience
Education
Duke University
Postdoctoral fellow
Advisor: Dr. Paul Magwene
2013-2016
University of Washington
Ph.D., Genome Sciences
Advisor: Dr. Joshua Akey
2007-2012
University of Wisconsin
B.S., Zoology
2001-2005
Experience
Computational Sciences, The Jackson Laboratory
Senior Computational Scientist
2021-present
Rosenthal Laboratory, The Jackson Laboratory
Research Scientist
2018-2021
Rosenthal Laboratory, The Jackson Laboratory
Associate Research Scientist
2016-2018
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Research HighlightOctober 20, 2020From one cell to trillions: Exploring early development
JAX researchers are probing the mysteries of pluripotent stem cells; the earliest stages of life. -
eNews
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Press ReleaseMay 20, 2019Must a high-fat diet lead to obesity-related metabolic syndrome?
Researchers say that harnessing a specific immune response to prevent inflammation could prevent insulin resistance, cardiovascular disease.