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Interpretable representation learning for 3D multi-piece intracellular structures using point clouds.

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Bibliographic Details
Title:	Interpretable representation learning for 3D multi-piece intracellular structures using point clouds.
Authors:	Vasan R; Allen Institute for Cell Science, Seattle, WA, USA., Ferrante AJ; Allen Institute for Cell Science, Seattle, WA, USA., Borensztejn A; Allen Institute for Cell Science, Seattle, WA, USA., Frick CL; Allen Institute for Cell Science, Seattle, WA, USA., Garrison P; Allen Institute for Cell Science, Seattle, WA, USA., Gaudreault N; Allen Institute for Cell Science, Seattle, WA, USA., Mogre SS; Allen Institute for Cell Science, Seattle, WA, USA., Mohammed FS; Allen Institute for Cell Science, Seattle, WA, USA., Morris B; Allen Institute for Cell Science, Seattle, WA, USA., Pires GG; Allen Institute for Cell Science, Seattle, WA, USA.; Altius Institute for Biomedical Sciences, Seattle, WA, USA., Saelid D; Allen Institute for Cell Science, Seattle, WA, USA., Rafelski SM; Allen Institute for Cell Science, Seattle, WA, USA., Theriot JA; Department of Biology and Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA., Viana MP; Allen Institute for Cell Science, Seattle, WA, USA. matheus.viana@alleninstitute.org.
Source:	Nature methods [Nat Methods] 2025 Jul; Vol. 22 (7), pp. 1531-1544. Date of Electronic Publication: 2025 Jul 03.
Publication Type:	Journal Article
Journal Info:	Publisher: Nature Pub. Group Country of Publication: United States NLM ID: 101215604 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1548-7105 (Electronic) Linking ISSN: 15487091 NLM ISO Abbreviation: Nat Methods Subsets: MEDLINE
Database:	MEDLINE Ultimate

Description
ISSN:	1548-7105
DOI:	10.1038/s41592-025-02729-9