Hongcheng Fan

This paper introduces spIsoNet, a deep-learning method to correct preferred-orientation bias in cryoEM reconstructions, demonstrating its effectiveness on influenza HA trimer datasets.

IsoNet2 reconstructs high-resolution 3D cellular structures from cryogenic electron tomography without averaging.

This paper determines the structural basis of motility in Shewanella oneidensis using cryoET and cryoEM, revealing molecular mechanisms of curvature generation and engineering principles for biomimetic systems.

The paper determines the cryoEM structure of PdpC, an effector protein from Francisella tularensis, and shows its binding to host phospholipids, revealing insights into its role in virulence.

This paper introduces spIsoNet, a deep-learning tool that improves 3D reconstruction isotropy and particle alignment in cryoEM by addressing the preferred orientation problem without altering specimen preparation.