What does research in computational biology look like, specifically at the intersection of deep learning and genomics? In this talk, we'll walk through an example research project to illustrate how comp-bio research can be driven by the knowns and unknowns of biology and how we can leverage deep learning to uncover biological insights. We'll begin with the concept of gene regulation: how our human bodies are made complex and kept alive by carefully orchestrated interactions between DNA and proteins. Other mammals have similar processes going on inside their cells - but how similar, exactly? Mice and humans both have hearts and lungs and livers, sure; but can we perform biological experiments in mice and reasonably expect the results to transfer to humans as well? We'll investigate this question through the lens of deep learning models trained to predict DNA-protein interactions. Note: no background in biology or machine learning is needed to follow this talk.
Speaker: Kelly Cochran, Stanford University
Johannes Eichstaedt, Stanford University, was originally scheduled to speak on this date.
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