NC BERD Seminar: Machine Learning for Precise Diagnostics and Therapeutics

NC BERD Seminar: Machine Learning for Precise Diagnostics and Therapeutics

Drug discoveries have been instrumental in improving global health over the last century, but the median drug now takes about 10 years to bring to market and costs over a billion dollars to develop. Rohit Singh, PhD, works to expedite the development of precise diagnostics and therapeutics by applying machine learning. In this seminar, Singh will outtline two recent research directions. In the first part, Singh uses single-cell multiomics to discover regulatory mechanisms governing the interaction between the epigenome, transcription factors, and target genes. This approach relies on methodological innovation, developing new Granger causal inference techniques to capitalize on the "parallax" between simultaneous but separate measures of cell state. In the second part, Singh will introduce the application of large language models to model protein interaction and function. These protein language models enable powerful new approaches to predicting and understanding protein-protein and protein-drug interactions. This seminar will conclude with a prospective look at how similar methods may help answer foundational questions in both basic and translational science.

Speaker:
Rohit Singh, PhD
Assistant Professor
Departments of Biostatistics & Bioinformatics and Cell Biology
Duke University

This event is sponsored by Duke University Departments of Computational Biology and Bioinformatics (CBB) and Biostatistics and Bioinformatics, the Duke Center for Genomic and Computational Biology (GCB), the Precision Genomics Collaboratory, and the Duke University School of Medicine. It is being cross-promoted by the North Carolina BERD Consortium (Duke University School of Medicine, University of North Carolina-Chapel Hill, and Wake Forest School of Medicine).