The center will develop the algorithms, software, and system architecture needed by biomedical scientists seeking to discover and represent causality using their large and diverse data sets.
We selected 3 very different biomedical problems to use as test beds for our algorithms and to drive the development of new algorithms that meet the needs of biomedical researchers.
We are implementing an integrated set of methods that support the graphical representation, discovery, and application of causal knowledge from large and complex biomedical data (see samples of structural causal
The Center for Causal Discovery is working together with other BD2K Centers to promote novel methods to analyze Big Data and to explore interoperability with tools and software developed by
Center for Causal Discovery Distinguished Lecture in Causal Discovery University of Pittsburgh, Carnegie Mellon University, Pittsburgh Supercomputing Center and Yale University Josh Stuart, PhD, Professor, Biomolecular Engineering Department, University of California Santa Cruz, “Unmasking All Forms of Cancer: Toward integrated maps of all tumor subtypes” at 11:00 am on Thursday, […]
The CCD will be represented by a team of 6 people at the BD2K All Hands Meeting on November 29-30, 2016 in Bethesda, MD. The 2016 BD2K All Hands Meeting will bring together researchers, educators, developers, and trainees funded by the BD2K Initiative. The goals of the All Hands Meeting are […]
Center for Causal Discovery Distinguished Lecture in Causal Discovery University of Pittsburgh, Carnegie Mellon University, Pittsburgh Supercomputing Center and Yale University Marloes Maathuis, PhD, Professor, Department of Statistics, ETH Zurich, Switzerland, “High-Dimensional Consistency in Score-Based and Hybrid Structure Learning ,” at 9:00 am on Friday, November 11, 2016, in Rooms 407A/B […]