Abstract
CRISPR genome editing has transformed biology by making it possible to alter DNA at precisely chosen locations. It is now a powerful research tool for testing how genes work and a growing therapeutic platform for personalized treatments for disease. However, realizing CRISPR’s potential depends on computational methods that can accurately measure editing outcomes, identify meaningful biological consequences, and guide the design of increasingly complex edits.
In this talk, I will share how computer science and bioinformatics can advance CRISPR research and therapeutic development. I will describe my work on CRISPResso2, an alignment-based software tool for interpreting sequencing data from genome-editing experiments. I will then discuss how CRISPR screens can model and study disease-associated mutations. Finally, I will look ahead to computational challenges in analyzing coordinated editing at multiple genomic targets for next-generation CAR T-cell therapies. Together, these examples illustrate how algorithms and biological experiments work together to make genome editing more precise, interpretable, and clinically useful.
Biography
Dr. Kendell Clement, PhD is an assistant professor in the Department of Biomedical Informatics at the University of Utah. He received a BS in Computer Science and Bioinformatics from Brigham Young University and was a Fulbright scholar at the Free University in Berlin. He completed a PhD in Medical Engineering from MIT and Harvard where he studied epigenetic changes in development and disease, particularly dysregulation of DNA methylation in blood cancers. He pursued postdoctoral research studies at the Massachusetts General Hospital where he developed software for analyzing genome editing experiments and collaborated with other groups in the development of next-generation genome editing tools such as base editors. Currently, his group is interested in developing new computational tools and everaging cutting-edge experimental technologies to understand the genetics and epigenetics of disease
initiation.