Part I. Framing the Discussion for the Day
Emily Carter, Dean of the Princeton University School of Engineering and Applied Science
Robert Hugin, Executive Chairman, Celgene
Dean Carter and Mr. Hugin start the day off with their views on why collaboration -- between industry, academia and other stakeholders in the biomedical data science space -- is crucial to innovation and to society.
Jennifer Rexford, Chair of Princeton's Computer Science Department
Professor Rexford sets the stage for the day by providing an overview of Princeton's core strengths in data science. Those strengths stretch from the discipline's technical foundations to capabilities that accelerate discovery across fields and that inform and guide societal impacts.
Leslie Greengard, Director of the Center for Computational Biology at the Flatiron Institute/Simons Foundation
Dr. Greengard reviews modeling, simulation and large-scale computing in biomedical data science. Greengard is also with the Courant Institute at NYU.
Nicolo Fusi, Research Scientist at Microsoft Research
Dr. Fusi outlines Microsoft's involvement in computational biology and starts by answering the question of why this topic is of interest to the company.
Part II. Research Presentations by Princeton Faculty
Professor Raphael presents recent research highlighting computational approaches his lab has developed to analyze interacting networks of mutations across cancer patients and to study tumor evolution within patients.
Professor Troyanskaya reviews her recent research focusing on a deep learning-based algorithmic framework to predict the effect of mutations in genomic sequence without any prior information and using these predictions to accurately prioritize disease-associated sequence variants.
Professor Singh presents her recent research focused on a method to identify genes whose interaction interfaces are enriched in somatic mutations, and to discover novel, relatively rarely-mutated genes with likely roles in cancer.
Professor Murphy outlines her recent research focused on the regulation of longevity and age-related declines, using the nematode C. elegans and human cells to help explain how long-lived animals are able to carry out functions for an extended time. Her work may help shed light on how to extend analogous functions in humans.
Jonathan D. Cohen
Professor Cohen presents his recent research combining imaging of brain function (from single neurons to whole brain activity) with modern methods from statistics and machine learning to measure, analyze, and simulate the brain’s own computations. His work through the Princeton Neuroscience Institute is designed to increase understanding of how the human brain works and has the potential to lead to new understanding and treatments of neurological dysfunction.
H. Sebastian Seung
Professor Seung describes his work focused on using techniques from deep learning and social computing to extract brain structure from microscope images. “EyeWire” showcases this approach by mobilizing gamers (yes, gamers.) from around the world to create 3D reconstructions of neurons by interacting with a deep convolutional network.
Professor Engelhardt reviews her recent research focused on models for the joint analysis of histopathological images and high-dimensional genomics data.