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Tracy Tran

University of Southern California - Department of Stem Cell Biology and Regenerative Medicine

Los Angeles, CA 90033

United States

SCHOLARLY PAPERS

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Scholarly Papers (1)

1.

Spatial Transcriptional Mapping of the Human Nephrogenic Program

Number of pages: 52 Posted: 15 Dec 2020
University of Southern California - Department of Stem Cell Biology and Regenerative Medicine, Flatiron Institute - Center for Computational Biology, Flatiron Institute - Center for Computational Biology, University of Southern California - Department of Stem Cell Biology and Regenerative Medicine, University of Southern California - Department of Stem Cell Biology and Regenerative Medicine, University of Southern California - Division of Biological Sciences, University of Southern California - Department of Stem Cell Biology and Regenerative Medicine, University of Edinburgh - MRC Human Genetics Unit, University of Southern California - Department of Stem Cell Biology and Regenerative Medicine, University of Southern California - Department of Stem Cell Biology and Regenerative Medicine, Flatiron Institute - Center for Computational Biology, Princeton University - Lewis-Sigler Institute for Integrative Genomics, Flatiron Institute - Center for Computational Biology, Flatiron Institute - Center for Computational Biology, Flatiron Institute - Center for Computational Biology, University of Southern California - Maternal Fetal Medicine Division, University of Southern California - Maternal Fetal Medicine Division, University of Southern California - Department of Stem Cell Biology and Regenerative Medicine, University of California, Los Angeles (UCLA) - Department of Molecular and Computational Biology, University of Southern California - Department of Stem Cell Biology and Regenerative Medicine, University of Edinburgh - MRC Human Genetics Unit, Princeton University - Lewis-Sigler Institute for Integrative Genomics and University of Southern California - Department of Stem Cell Biology and Regenerative Medicine
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Abstract:

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Human kidney, development, disease, single cell, spatial mapping, nephrogenesis, gene regulatory networks, machine learning, image registration