Joanne C. Beer

NULISA is a proteomic platform with attomolar sensitivity and high multiplexing, enabling detection of low-abundance proteins in liquid biopsies.

This paper shows that removing scanner effects in mean and variance is insufficient for multivariate pattern analysis and proposes a method to harmonize covariance across scanners.

The paper develops a connectivity-based electric-field modelling approach to identify individualized TMS targets for depression treatment by combining rsFC and e-field simulations.

The paper examines how different psychopathology dimensions affect various scales of brain functional connectivity using multiple modeling approaches.

The paper introduces longitudinal ComBat to harmonize multi-scanner imaging data, showing it improves detection of longitudinal changes and controls type I error better than existing methods.