2025/12/11 by Yun-Tao Liu, Hongcheng Fan, Jonathan Jih +3 · 1 voice · 4 citations
Biochemistry, Genetics and Molecular Biology · #Advanced Electron Microscopy Techniques and Applications #RNA and protein synthesis mechanisms #ATP Synthase and ATPases Research
paper · doi:10.64898/2025.12.09.693325
Abstract We introduce IsoNet2 , an end-to-end self-supervised deep-learning method that directly reconstructs high-quality 3D densities from cryogenic electron tomography. A unified network simultaneously performs denoising, contrast transfer function correction, and missing-wedge restoration, achieving ∼20 Å resolution without averaging. A feature-rich GUI enables rapid, dataset-specific fine-tuning for end-users. IsoNet2 resolves domain organization in HIV capsid proteins, tRNA occupancy in individual ribosomes, and in situ architectures of mitochondrial respiration-related complexes, enabling atomic-level interpretation of cellular environments.