  Structure learning offers an expressive, versatile and explainable approach
to causal and mechanistic modeling of complex biological data. We present
wiseR, an open source application for learning, evaluating and deploying robust
causal graphical models using graph neural networks and Bayesian networks. We
demonstrate the utility of this application through application on for
biomarker discovery in a COVID-19 clinical dataset.
