Steve Horvath is a UCLA professor and the recipient of several research awards, including an Allen Distinguished Investigator award. His methodological research area lies at the intersection of biostatistics, bioinformatics, computational biology, cancer research, genetics, epidemiology, machine learning, and systems biology. His group work both on supervised and unsupervised machine learning methods. The first multi-tissue epigenetic clock, Horvath's epigenetic clock, was developed by Steve Horvath
|Name Work||Domain||Description work||Source|
|Reversal of aging in human cells||Genomics||
Transient non-integrative nuclear reprogramming promotes multifaceted reversal of aging in human cells. Recent evidence has shown that transient transgenic reprogramming can ameliorate age-associat...
Steve Horvath, PhD, ScD is a professor of human genetics and biostatistics at UCLA's Fielding School of Public Health. Dr. Horvath is the creator of the Horvath Epigenetic Aging Clock. His work incorporates elements of biostatistics, genetics, epidemiology, epigenomics, and other fields of study. He applies his understanding of this diverse range of disciplines to study a spectrum of chronic diseases, including cancer, cardiovascular disease, neurodegenerative disease, and other diseases of aging. Dr. Horvath's so-called "pan-tissue epigenetic aging clock" is an algorithm that accurately predicts a person's chronological age from marks on the DNA across multiple cells, tissues, and organs, and even mammalian species. Further refining this initial algorithm, Dr. Horvath built on this to develop second-generation clock algorithm that could predict time-to-death among people of the same chronological age, as well as lifespan and healthspan. One of these clocks, the GrimAge clock, is named deliberately after its connotation: predicting time until death ("Grim"). In this episode, Dr. Steven Horvath describes epigenetic clocks and their role in predicting – and possibly slowing – aging