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Interpretable Deep Learning for Cancer Personalized Medicine

Engineering & Science Building 048 Vanderbilt University, Nashville

In recent years, deep learning models have resulted in outstanding breakthrough performances. However, many models behave as black boxes that can hide data biases, incorrect hypotheses or even software errors. In this talk, I will illustrate how interpretable deep learning models can achieve both high prediction accuracy and transparency. First, I will introduce multi-modal deep […]

Building the Cell from Unreliable Parts: the Case of Stochastic Organelle Biogenesis

Engineering & Science Building 048 Vanderbilt University, Nashville

Perhaps the defining feature of the eukaryotic cell is its organization into membrane-bound compartments known as organelles. While the processes underlying the biogenesis of individual organelles are often well-known the precision with which individual cells exert quantitative control over individual organelle properties, such as number and size, and coordinate these properties at systems-scale across the […]

Expanding the Genomechanics Toolbox: New Techniques to Investigate Metastatic Mechanical and Genetic Data at Single Cell Level across the Genome

Engineering & Science Building 048 Vanderbilt University, Nashville

Nine out of every ten cancer-related deaths is caused by metastasis, but the molecular mechanisms driving this process are still not fully understood. Several studies have implicated that as a cell’s metastatic potential increases, cell stiffness decreases. Yet while certain genes that affect cell mechanics have been studied, a genome-wide study of networks that modulate […]