WikiSysop: Created page with "== Citation == M. Joosten, J. Greer, J. Parkhurst, T. Burnley, and A. J. Jakobi, “Roodmus: A toolkit for benchmarking heterogeneous electron cryo-microscopy reconstructions,” IUCrJ, vol. 11, no. 6, 2024. == Abstract == Conformational heterogeneity of biological macromolecules is a challenge in single-particle averaging (SPA). Current standard practice is to employ classification and filtering methods that may allow a discrete number of conformational states to be..."

2024-11-08T09:46:08Z

Created page with "== Citation == M. Joosten, J. Greer, J. Parkhurst, T. Burnley, and A. J. Jakobi, “Roodmus: A toolkit for benchmarking heterogeneous electron cryo-microscopy reconstructions,” IUCrJ, vol. 11, no. 6, 2024. == Abstract == Conformational heterogeneity of biological macromolecules is a challenge in single-particle averaging (SPA). Current standard practice is to employ classification and filtering methods that may allow a discrete number of conformational states to be..."

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== Citation ==

M. Joosten, J. Greer, J. Parkhurst, T. Burnley, and A. J. Jakobi, “Roodmus: A toolkit for benchmarking heterogeneous electron cryo-microscopy reconstructions,” IUCrJ, vol. 11, no. 6, 2024.

== Abstract ==

Conformational heterogeneity of biological macromolecules is a challenge in
single-particle averaging (SPA). Current standard practice is to employ classification
and filtering methods that may allow a discrete number of conformational
states to be reconstructed. However, the conformation space accessible to
these molecules is continuous and, therefore, explored incompletely by a small
number of discrete classes. Recently developed heterogeneous reconstruction
algorithms (HRAs) to analyse continuous heterogeneity rely on machinelearning
methods that employ low-dimensional latent space representations.
The non-linear nature of many of these methods poses a challenge to their
validation and interpretation and to identifying functionally relevant conformational
trajectories. These methods would benefit from in-depth benchmarking
using high-quality synthetic data and concomitant ground truth
information. We present a framework for the simulation and subsequent
analysis with respect to the ground truth of cryo-EM micrographs containing
particles whose conformational heterogeneity is sourced from molecular
dynamics simulations. These synthetic data can be processed as if they were
experimental data, allowing aspects of standard SPA workflows as well as
heterogeneous reconstruction methods to be compared with known ground
truth using available utilities. The simulation and analysis of several such
datasets are demonstrated and an initial investigation into HRAs is presented.

== Keywords ==

== Links ==

https://journals.iucr.org/m/issues/2024/06/00/rq5011/index.html

== Related software ==

== Related methods ==

== Comments ==

2024Joosten Roodmus - Revision history