(Click image for presentation slides) Role of a Scientific Catalyst… As a Scientific Catalysts, we see your role as a hub person for your site who broadcasts our activities to other investigators at your site so that they can utilize: 1. training opportunities, 2. software tools and 3. other useful […]
Susan Athey, PhD Stanford University This talk will cover a pair of papers that modify popular machine learning methods for application to estimating how treatment effects vary with observable unit characteristics. Applications include large scale field experiments or online A/B tests. The first paper develops ?causal trees,? a modification of[…]
There are many actions researchers can take to increase the openness and reproducibility of their work. Please join us for a workshop, hosted by the Center for Open Science, to learn easy, practical steps researchers can take to increase the reproducibility of their work. The workshop will be hands-on. Using[…]
Frederick Eberhardt, PhD, Professor of Philosophy, Cal Tech
Karen Sachs, PhD Research Scientist in the School of Medicine, Stanford University “Causal Learning in Signaling Networks”
Presenter: Kun Zhang, PhD, Assistant Professor of Philosophy, Carnegie Mellon University Paper: TBA
Teresa M. Przytycka, PhD, Senior Investigator, Algorithmic Methods in Computational and Systems Biology (AlgoCSB), National Center for Biotechnology Information, National Institutes of Health “Understanding Genotype-Phenotype Relations via Network Approaches”
Ben Raphael, PhD, Brown University Advances in DNA sequencing technology have enabled large-scale measurement of the molecular alterations that occur in cancer cells. Translating this information into deeper insights about processes that drive cancer development demands novel computational approaches. In this talk, I will describe algorithms to address two key problems[…]