Yoseph Barash is a computational biologist who works on predictive models to understand RNA biogenesis, its regulation and its role in human disease. His lab, the BioCiphers lab, develops AI, machine learning, and statistical algorithms that integrate genomic and genetic data, followed by wet lab experimental verifications.

Barash earned a B.Sc. and a Ph.D. in machine learning under Nir Friedman at the Hebrew University in 2006. He did his postdoctoral work with Ben Blencowe and Brendan Frey at the University of Toronto, focusing on alternative splicing of RNA. His postdoctoral work led to the first predictive models for splicing variations as a function of the cellular condition and genetic variations. In 2012, Barash moved to the University of Pennsylvania, where he became a full professor with tenure in the medical school’s Department of Genetics and the engineering school’s Department of Computer and Information Science.

Barash’s lab was the first to offer tools for mapping, quantifying, and visualizing complex splicing variations, showing these comprise over 30 percent of the human transcriptome variations. The lab’s research has also expanded to analysis and modeling of UTR regulatory elements  as well as creating new high-throughput assays (Yang et al NAR 2024). The BioCiphers lab’s tools to quantify and predict aberrant splicing have been instrumental in studying RNA splicing defects in cancer, immunotherapy, and other disease (e.g. Sotillo et al Cancer Discovery 2015, Rivera et al PNAS 2021) and have been licensed by dozens of companies. Since 2020, Barash has been advising several companies in the RNA therapeutics space.