Roles
Research Associate Professor, Pending Rank
Assistant Director, Cancer Modeling Shared Resource
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Biography
Dr. Sang Yong Kim is a research associate professor in the department of pathology and laboratory medicine at the University of Miami, Miller School of Medicine and serves as scientific director of the transgenic and genetic engineering mouse program within the cancer modeling shared resource (CMSR). With more than three decades of experience in developmental biology and genome engineering, Dr. Kim has contributed to thousands of genetically engineered mouse models (GEMMs) that have accelerated discoveries in cancer genetics and stem cell biology.
Dr. Kim has extensive expertise in the design and generation of GEMMs, including CRISPR/Cas9 mediated genome editing and transgenic mouse model development. His technical strengths encompass CRISPR/Cas9 editing, embryonic stem (ES) cell gene targeting, reversible RNA interference systems, BAC transgenics, conditional alleles, and stem cell–derived GEMMs technologies. Together, these platforms enable precise, scalable, and reproducible in vivo modeling across a wide range of biological and disease contexts. Dr. Kim’s work has been published in leading scientific journals, including Nature, Cell, and Science. He is also affiliated with the Sylvester Comprehensive Cancer Center, where he supports interdisciplinary cancer research through advanced mouse modeling and genetic engineering strategies. -
Research Interests
Dr. Kim’s research centers on mammalian genome engineering to develop precise and biologically relevant in vivo models of human disease. His work employs CRISPR/Cas9 genome editing, embryonic stem cell gene targeting, conditional alleles, and BAC transgenics to study the genetic mechanisms driving cancer, aging, and tissue-specific biology. He is particularly interested in understanding how age-associated genomic instability promotes tumor initiation and progression, as well as developing enhancer-based gene expression strategies combined with non-viral gene delivery systems to introduce targeted genetic alterations directly into developing or adult tissues.
His future research aims to integrate AI-driven, automated single-cell selection and classification approaches focused on sperm cells to study male germline aging, genome surveillance, and mutational burden. Because the male germline undergoes continual cell division throughout life, sperm cells progressively accumulate somatic mutations, epigenetic drift, and DNA damage, reflecting age-associated declines in genome maintenance and repair fidelity. By leveraging single-sperm-cell DNA methylation patterns and genomic features, this work seeks to identify signatures of impaired genome surveillance and increased mutational burden that are predictive of cancer risk.