Knowles Lab
The Knowles Lab opened in January 2019 at the New York Genome Center, jointly with Columbia University. The lab uses statistical machine learning—probabilistic graphical models, deep learning, causal network inference and convex optimization—to address challenges in understanding large genomic datasets. They develop computational and experimental methods to map the causes and consequences of transcriptomic dysregulation, especially aberrant splicing, across the spectrum from rare to common genetic disease. They collaborate with groups at NYGC, Columbia, MSSM, and beyond, focusing on understanding the genetic and transcriptomic basis of neurological diseases, both degenerative and psychiatric, and more recently, cancer.
David A. Knowles, PhD
Core Faculty Member, NYGC
Assistant Professor, Computer Science, Columbia University; Interdisciplinary Appointee, Systems Biology, Columbia University; Affiliate Member, Data Science Institute, Columbia University
Latest News & Publications
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Computational Biology and Chemistry · November 16, 2024
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Genome Biology · December 18, 2023
Smoother: a unified and modular framework for incorporating structural dependency in spatial omics data.
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bioRxiv · November 16, 2023 · Preprint
A Bayesian framework for inferring dynamic intercellular interactions from time-series single-cell data.