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Model improves classification quality by selecting reliable particles in cryo-EM analysis, suggesting better outcomes.
The model identifies and removes deformed or misclassified particles to improve classification quality. It serves as a data-filtering post-processing step following 2D classification. By improving the quality of particle datasets, it enhances the reliability of subsequent analysis in cryo-EM.
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Wang et al. (2026) studied this question.
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