School of Medicine
Showing 11-20 of 25 Results
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Jou-Ho Shih
Postdoctoral Scholar, Genetics
Bio2011 B.S., Life Science, National Tsing Hwa University, Taiwan
2019 Ph.D., Genome and Systems Biology Degree Program, National Taiwan University, Taiwan; Advisor: Dr. Yuh-Shan Jou
2019-2020 Postdoctoral Fellow, Biomedical Science, Academia Sinica, Taiwan; Advisor: Dr. Yuh-Shan Jou
2020-present Postdoctoral Fellow, Dept. Genetics, Stanford University, CA; Advisor: Dr. Michael Snyder -
Mahasish Shome
Postdoctoral Scholar, Genetics
BioDr. Mahasish Shome is interested in understanding the underlying mechanism of disease progression. He uses various omics profiling to identify biomarkers relevant to the disease. He studies antibodies, cytokines, proteins and metabolites profile to decipher the connection of disease with markers. This helps in early diagnosis, understanding disease state and drug/vaccine effectiveness.
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Arend Sidow
Professor of Pathology and of Genetics
On Leave from 04/01/2024 To 02/21/2025Current Research and Scholarly InterestsWe have a highly collaborative research program in the evolutionary genomics of cancer. We apply well-established principles of phylogenetics to cancer evolution on the basis of whole genome sequencing and functional genomics data of multiple tumor samples from the same patient. Introductions to our work and the concepts we apply are best found in the Newburger et al paper in Genome Research and the Sidow and Spies review in TIGS.
More information can be found here: http://www.sidowlab.org -
Michael Snyder, Ph.D.
Stanford W. Ascherman Professor of Genetics
On Partial Leave from 12/02/2024 To 12/01/2025Current Research and Scholarly InterestsOur laboratory use different omics approaches to study a) regulatory networks, b) intra- and inter-species variation which differs primarily at the level of regulatory information c) human health and disease. For the later we have established integrated Personal Omics Profiling (iPOP), an analysis that combines longitudinal analyses of genomic, transcriptomic, proteomic, metabolomic, DNA methylation, microbiome and autoantibody profiles to monitor healthy and disease states