A collaborative paper of three members of the Benos Lab was accepted for publication by the journal Frontiers in Epidemiology. The paper is entitled “Causal Discovery in High-dimensional, Multicollinear Datasets”. As the title says, this paper addresses two important problems of causal discovery. Different methods for dimensionality reduction are compared on simulated data and the utility of the method is demonstrated in a real-life COVID-19 dataset, This represents is an important advance in the causal discovery field.
Congratulations Minxue, Daniel and Tyler!