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., Gaudreault N; Allen Institute for Cell Science, Seattle, WA, USA., Mogre SS; 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., 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.
Source: BioRxiv : the preprint server for biology [bioRxiv] 2024 Aug 13. Date of Electronic Publication: 2024 Aug 13.
Publication Type: Journal Article; Preprint
Journal Info: Country of Publication: United States NLM ID: 101680187 Publication Model: Electronic Cited Medium: Internet ISSN: 2692-8205 (Electronic) Linking ISSN: 26928205 NLM ISO Abbreviation: bioRxiv Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:2692-8205
DOI:10.1101/2024.07.25.605164