A Bayesian Framework for Cryo-EM Heterogeneity Analysis using Regularized Covariance Estimation.

ABSTRACT: Proteins and the complexes they form are central to nearly all cellular processes. Their flexibility, expressed through a continuum of states, provides a window into their biological functions. Cryogenic-electron microscopy (cryo-EM) is an ideal tool to study these dynamic states as it captures specimens in non-crystalline conditions and enables high-resolution reconstructions. However, analyzing the heterogeneous distribution of conformations from cryo-EM data is challenging. Current methods face issues such as a lack of explainability, overfitting caused by lack of regularization, and a large number of parameters to tune; problems exacerbated by the lack of proper metrics to evaluate or compare heterogeneous reconstructions. To address these challenges, we present RECOVAR, a white-box me

SUBMITTER: Gilles MA 

PROVIDER: S-EPMC10634927 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature