WikiSysop: Created page with "== Citation == Lauzirika, O., Pernica, M., Herreros, D., Ramı́rez-Aportela, E., Krieger, J., Gragera, M., Iceta, M., Conesa, P., Fonseca, Y., Jiménez, J., Flipovic, J., Carazo, J.M. and Sorzano, C.O.S. 2025. How many (distinguishable) classes can we identify in single-particle analysis? Acta Crystallographica Sec. D. 81, 10 (2025). == Abstract == Heterogeneity in cryoEM is essential for capturing the structural variability of macromolecules, reflecting their functi..."

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Created page with "== Citation == Lauzirika, O., Pernica, M., Herreros, D., Ramı́rez-Aportela, E., Krieger, J., Gragera, M., Iceta, M., Conesa, P., Fonseca, Y., Jiménez, J., Flipovic, J., Carazo, J.M. and Sorzano, C.O.S. 2025. How many (distinguishable) classes can we identify in single-particle analysis? Acta Crystallographica Sec. D. 81, 10 (2025). == Abstract == Heterogeneity in cryoEM is essential for capturing the structural variability of macromolecules, reflecting their functi..."

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== Citation ==

Lauzirika, O., Pernica, M., Herreros, D., Ramı́rez-Aportela, E., Krieger, J., Gragera, M., Iceta, M., Conesa, P., Fonseca, Y., Jiménez, J., Flipovic, J., Carazo, J.M. and Sorzano, C.O.S. 2025. How many (distinguishable) classes can we identify in single-particle analysis? Acta Crystallographica Sec. D. 81, 10 (2025).

== Abstract ==

Heterogeneity in cryoEM is essential for capturing the structural variability of
macromolecules, reflecting their functional states and biological significance.
However, estimating heterogeneity remains challenging due to particle misclassification
and algorithmic biases, which can lead to reconstructions that
blend distinct conformations or fail to resolve subtle differences. Furthermore,
the low signal-to-noise ratio inherent in cryo-EM data makes it nearly impossible
to detect minute structural changes, as noise often obscures subtle variations
in macromolecular projections. In this paper, we investigate the use of
p-values associated with the null hypothesis that the observed classification
differs from a random partition of the input data set, thereby providing a
statistical framework for determining the number of distinguishable classes
present in a given data set.

== Keywords ==

== Links ==

https://journals.iucr.org/d/issues/2025/10/00/vo5020/index.html

== Related software ==

== Related methods ==

== Comments ==

2025Lauzirika Distinguishable - Revision history