Speaker: Prof David Knowles, Columbia University
Title: ‘Probabilistic models of transcriptomic dysregulation in human genetic disease’
Abstract: Gene regulation is tightly regulated in healthy human development but frequently dysregulated in disease. RNA-seq has become ubiquitous for assaying the transcriptome: the collection of messenger RNA molecules expressed from the genes of an organism. However, significant computational and statistical challenges remain to translate the resulting noisy, confounded RNA-seq data into meaningful understanding of the biological system or disease state under consideration. I will describe our use of probabilistic models, deep learning and convex optimization to address such challenges.
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