Data Science for Translational Research

Dr. Debashis Sahoo, PhD

Associate Professor

Pediatrics and Computer Science and Engineering

University of California San Diego

11/17/2023

11AM – 12PM CST

Location: UTSA Main Campus, Student Union Hidalgo Room (2.214)

Zoom: https://utsa.zoom.us/j/91049981814

Translational research aims to swiftly apply basic science discoveries in practical healthcare. Productivity hurdles can impede the quick translation of research into healthcare breakthroughs, with issues like reproducibility and generalizability of biological results in clinical settings posing significant challenges. Concerns about irreproducible results are on the rise, with over 70% of researchers reportedly facing challenges reproducing others’ experiments, and more than half struggling with their own. Drug development, a crucial facet of translational research, maintains a low success rate despite past efforts.

Part of the problem lies in the tools of data science and statistics used. I’ll introduce you to a new approach—Boolean analysis of large and diverse biological datasets. In my research group, we’ve pioneered this method and developed computational tools to uncover invariant logical relationships between genes. Join me as we explore how leveraging these invariant relationships can enhance the reproducibility of current approaches. We will discuss how Boolean analysis can transform the power of AI/ML approaches.