Gerald M. Pao

This paper introduces Generative Manifold Networks (GMNs) for modeling complex system dynamics, demonstrating their ability to predict and simulate chaotic and neural dynamics with explainability.

The paper shows that causal relationships can exist in transcriptional networks without correlation, using nonlinear causality tests to detect uncorrelated causal links in yeast and mouse.

This paper extends empirical dynamic modeling to cross-sectional data by using random data projection and validates it on simulated data.

This study identifies PBLOprm1 neurons as critical for opioid-induced respiratory depression and shows their activation can rescue respiratory rhythms.

This paper demonstrates the manipulation of the optical refractive index in mammalian cells using cephalopod reflectin protein nanoparticles and shows their application in microscopy techniques.

This study identifies a novel neural circuit involving PBLOprm1 neurons that regulates breathing, pain, and anxiety by linking limbic signals to respiratory control.