Center for Causal Discovery (CCD) Training Plan Overview Joe Ayoob, Training Component Co-I June 24, 2015 Center Director: Greg Cooper Training Component.

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Presentation transcript:

Center for Causal Discovery (CCD) Training Plan Overview Joe Ayoob, Training Component Co-I June 24, 2015 Center Director: Greg Cooper Training Component C0-Leaders: Richard Scheines Ivet Bahar

CCD Goals Develop algorithms to discover causal relationships and networks from large and diverse types of biomedical data and background knowledge, i.e., big data

Develop CD algorithms for very large biomedical data sets in DBPs… Cancer driver mutations -tumor genomes, gene/microRNA expression data… Lung fibrosis driving factors -tissue images, gen-/transcript-/methyl-omes… -clinical phenotypes: lung function, smoking history… Functional brain connectivity -fMRI data: autism spectrum, schizophrenia, neurotypicals Disseminate: algorithms, software, tools Train:Data Scientists to develop and apply CCD tools to biomed. Q’s Biomedical Scientists to use CCD tools to discover causality CCD Goals

Activities Hold regular meetings Maintain an active website Infuse Big Data themes into existing training programs/courses Create new online course on Causal Discovery in Biomedicine Host Summer Short Course on causal graphical modeling Present workshops on causal modeling Invite distinguished seminar speakers Support users of CCD tools, algorithms, and software

CCD Website

Online Resources

Nascent Scientists Summer programs for UG & HS Intro big data research at early stages Infuse Big Data themes into classes Students work with CCD investigators Students work on Big Data problems

Graduate Courses Integrate and Augment Causal Discovery topics in existing courses In 3 major programs: Logic, Computation, and Methodology program Logic, Computation, and Methodology program (CMU) Computational Biology program Computational Biology program (CMU-Pitt) Biomedical Informatics program Biomedical Informatics program (Pitt) Develop a new online course on Causal Discovery in Biomedicine -Will be offered through above 3 programs and CMU Open Learning Initiative -Accessible to Data Scientists and Biomedical Investigators -Will integrate Causality Lab software, new tutorials, CCD biomedicalCausality Lab software examples and case studies.

Summer Short Course incl. people from industry, tech, govmnt. ~90 registrations 65 attendees

Summer Short Course Testimonials from Casual Discovery with Graphical Models Summer Short Course: This course is amazing and the information is very important. I wish there were more resources available outside of this training. The hands-on exercises were very useful. Instructors were great! This one of the best, most exciting courses I have ever taken, and I have over 23 years of formal education. Excellent team of instructors and the organization of course was perfect. Most valuable: Hands-on component and help from TAs Place to improve: Tuning to the proper level to reach the diverse audience

Summer Short Course

+ Workshops TBA - shorter short course - some existing materials - at conferences & possibly partner institutions Lignam and algorigthms to detect cycles – Joe Ramsey Feedback/time series – David Danks

Distinguished Lecture Series

Online Support Coming soon… Remote support through website – documentation & training videos Software webinars – live, interactive demos of software (archived) Developer office hours – direct access to CCD software developers CCD Journal Club