Jarret Glasscock
Geneticist and computational biologist leveraging RNA for precision medicine
Summary
Jarret Glasscock is a pioneer in genomics and computational biology, deeply involved in foundational projects like the Human Genome Project. His early work included characterizing the first RNA-seq experiments and publishing one of the first cancer genomes (Acute Myeloid Leukemia) in 2008, establishing his expertise in leveraging genomic data for medical insights. medcitynews+2
As the co-founder of Cofactor Genomics, Jarret has transitioned from CEO to President & CTO, leading the company's mission to transform precision medicine through RNA-based diagnostics. He has focused on developing predictive immune models and multidimensional biomarkers to improve patient response to immunotherapies, a critical area with significant unmet clinical needs. cofactorgenomics+2
Beyond his entrepreneurial endeavors, Jarret has contributed to the venture capital landscape as a Senior Venture Partner at Pioneer Fund, supporting early-stage companies in the healthcare and biotech sectors. This role demonstrates his commitment to fostering innovation within the scientific and medical communities. nfx
Glasscock's personal background, including growing up skateboarding and his Navajo heritage, has influenced his perspective. He views the challenges of entrepreneurship through the lens of persistence learned from skateboarding and is driven by a desire to make healthcare technologies more accessible to individuals, reflecting a broad, impact-oriented mindset. entrepreneurquarterly
Work
Education
Writing
DNA sequencing of a cytogenetically normal acute myeloid leukaemia genome
January 1, 2008Co-authored one of the first papers on sequencing a cancer genome (Acute Myeloid Leukemia), published in Nature in 2008.
ScriptSure: Computational analysis of human ESTs translates to an informative representation of the transcript data
January 1, 2004His PhD thesis, focusing on the computational analysis of expressed sequence tags (ESTs) to create informative representations of the human transcriptome.