UM-CPP: A Universal Model for Efficient Classification of Protein Particles in cryo-EM Micrographs with Feature Engineering.

ABSTRACT: Cryo-electron microscopy (cryo-EM) is a powerful tool for high-resolution structural analysis of proteins and viruses. However, a major challenge in cryo-EM data processing is the presence of heterogeneous samples, IC contamination, and extraneous impurities, which hinder accurate target protein identification. To address this issue, we propose the Universal Model for Cryo-electron Microscopy Particle Picking (UM-CPP), a novel framework that integrates feature engineering with deep learning to enhance particle detection in cryo-EM micrographs. The key contribution of UM-CPP lies in its hybrid approach, which combines classical machine learning features with state-of-the-art deep learning techniques. This fusion enables robust and adaptable performance across diverse protein structures whil

SUBMITTER: Yao Z 

PROVIDER: S-EPMC12268404 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature