Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Cell shapes decode molecular phenotypes in image-based spatial proteomics.

Cell systems - 17 Jun 2026

Le Trang, Leineweber William D, Viana Matheus P, Cesnik Anthony, Hansen Jan N, Ouyang Wei, Rafelski Susanne M, Lundberg Emma

Abstract excerpt

Cellular and tissue structures arise from a few cell shapes, which undergo transformations based on biophysical constraints. Despite links between signaling pathways and cellular geometry, whole-proteome orchestration in association with cell shape is underexplored. In this study, over 1 million single cells stained for 11,998 proteins across 11 cell lines in the Human Protein Atlas were analyzed for organelle,...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Cell Line
Share to Cell Shape
Share to Phenotype

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Proteome

Share to Proteomics

Share to Signal Transduction

Source

Open in PubMed Open full text

Identifiers

PMID: 42013840
DOI: 10.1016/j.cels.2026.101589
PMCID: PMC13138879

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 2 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Cell shapes decode molecular phenotypes in image-based spatial proteomics.PMID 42013840Read ↗

Cell shapes decode molecular phenotypes in image-based spatial proteomicsSemantic proximity Read ↗

Cellular Morphometric Analysis (CellMorph)-a comprehensive imaging-based tool for quantifying cellular phenotype heterogeneity and dynamics across biological processes.Semantic proximity Read ↗

Subcellular Region Morphology Reflects Cellular IdentitySemantic proximity Read ↗

3D single-cell shape analysis using geometric deep learningSemantic proximity Read ↗

Generative machine learning unlocks the first proteome-wide image of human cellsSemantic proximity Read ↗

Cell-TIMP: Cellular Trajectory Inference based on Morphological ParameterSemantic proximity Read ↗

Multiplexed high-content imaging uncovers morphological diversity of lymphocyte activation and dysfunctionSemantic proximity Read ↗

Single cell spatial proteomics maps human liver zonation patterns and their vulnerability to fibrosisSemantic proximity Read ↗

CellScope: High-Performance Cell Atlas Workflow with Tree-Structured RepresentationSemantic proximity Read ↗

A genome-wide atlas of human cell morphologySemantic proximity Read ↗

Robust integrated intracellular organization of the human iPS cell: where, how much, and how variableSemantic proximity Read ↗

Validation of Morphology-Guided Computational Enhancement for Single-Cell Resolution Spatial TranscriptomicsSemantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.