CABB is a workshop at IEEE BIBM 2019, and will be occurring on Nov 21 in San Diego, California. It will promote the application of causal discovery and related methods in bioinformatics and biomedicine, identify challenges in bioinformatics and biomedicine that require the development of new causally informed algorithms, guide the field of causal analysis towards establishing best practices for the bioinformatics and biomedical domains, and provide a venue for causal analysis researchers to share and communicate their findings.
Research topics included in the workshop
- Development and/or improvement of automated causal discovery methods for biomedical data
- Application or evaluation of automated causal discovery methods in the domain of biomedicine or bioinformatics
- Causal effect estimation from biomedical data guided by data driven causal structure discovery
- Predictive modeling applications in bioinformatics and biomedicine guided by causal structure discovery
- Causal discovery leveraging combined information in prior knowledge, observational data and experimental data, and/or using data from multiple sources, measurement granularity, and data distributions
Keynote speaker
- Greg Cooper
Important dates
Oct 15Oct 22, 2019: Notification of paper acceptance to authors- Nov. 1, 2019: Camera-ready of accepted papers
- Nov. 21, 2019: CABB Workshop
Program Chairs or co-chairs:
- Sisi Ma
- Erich Kummerfeld
Program Committee Members
- Peter Spirtes
- Frederick Eberhardt
- Joseph Ramsey
- Bryan Andrews
- Fattaneh Jabbari
- Dan Malinsky
- Jean Krivine
- Shohei Shimizu
- Karen Sachs
- Joris Mooij
- Biwei Huang
Causal Analytics for Bioinformatics and Biomedicine (CABB) 