The CAHRA Challenge: A Community-Wide Assessment of Cryo-EM Heterogeneous Reconstruction Algorithms
- 1Princeton University
Abstract
The ability of cryo-electron microscopy (cryo-EM) to interrogate the atomic structure and motion of biomolecules has motivated the development of a wide range of algorithms for heterogeneity analysis. However, evaluating and comparing these methods remains challenging because ground-truth structures are generally unknown for experimental samples. Here, we introduce the 2026 Community-Wide Assessment of Heterogeneous Reconstruction Algorithms (CAHRA), a community-wide challenge centered on three benchmark datasets that probe distinct tasks in heterogeneity analysis. These include (1) compositional heterogeneity arising from mixtures of distinct protein complexes, (2) continuous conformational variability and atomic modeling, and (3) entanglement between molecular conformation and particle pose. We describe the design, construction, and validation of these datasets, as well as their use in the recently completed CAHRA Challenge.
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BibTeX
@misc{feathers2026cahra,
title = {{The CAHRA Challenge: A Community-Wide Assessment of Cryo-EM Heterogeneous Reconstruction Algorithms}},
author = {J. R. Feathers and R. Heeter and G. Woollard and S. M. Hanson and P. Cossio and J. Greer and T. Burnley and E. Zhong},
howpublished = {bioRxiv},
year = {2026},
month = sep,
doi = {10.64898/2026.09.15.751515},
url = {https://www.biorxiv.org/content/10.64898/2026.09.15.751515v1},
note = {CC BY},
}
RIS
TY - UNPB
TI - The CAHRA Challenge: A Community-Wide Assessment of Cryo-EM Heterogeneous Reconstruction Algorithms
AU - J. R. Feathers
AU - R. Heeter
AU - G. Woollard
AU - S. M. Hanson
AU - P. Cossio
AU - J. Greer
AU - T. Burnley
AU - E. Zhong
PY - 2026
DA - 2026/09/15
PB - bioRxiv
DO - 10.64898/2026.09.15.751515
UR - https://www.biorxiv.org/content/10.64898/2026.09.15.751515v1
AB - The ability of cryo-electron microscopy (cryo-EM) to interrogate the atomic structure and motion of biomolecules has motivated the development of a wide range of algorithms for heterogeneity analysis. However, evaluating and comparing these methods remains challenging because ground-truth structures are generally unknown for experimental samples. Here, we introduce the 2026 Community-Wide Assessment of Heterogeneous Reconstruction Algorithms (CAHRA), a community-wide challenge centered on three benchmark datasets that probe distinct tasks in heterogeneity analysis. These include (1) compositional heterogeneity arising from mixtures of distinct protein complexes, (2) continuous conformational variability and atomic modeling, and (3) entanglement between molecular conformation and particle pose. We describe the design, construction, and validation of these datasets, as well as their use in the recently completed CAHRA Challenge.
ER -