Center for Causal Discovery (CCD)

Training Plan Overview

Joe Ayoob, Training Component Co-I

June 24, 2015

Center Director: Greg CooperTraining 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’sBiomedical 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 (CMU)Computational Biology program (CMU-Pitt)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 biomedical

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 TAsPlace to improve: Tuning to the proper level to reach the diverse audience

Summer Short Course

Summer Short Course

+ Workshops TBA - shorter short course - some existing materials - at conferences & possibly partner institutions

Lignam and algorigthms to detect cycles – Joe RamseyFeedback/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