Nano-org, a functional resource for single-molecule localisation microscopy data

The nanoscale organisation of proteins plays a key role in diverse cellular processes, including signalling, adhesion, and structural integrity. Single-molecule localisation microscopy (SMLM) is a super-resolution imaging technique that captures the spatial distributions of proteins in cells with nanometre precision, enabling detailed studies of protein clustering and architecture. However, comparing such data across experiments remains challenging due to a lack of curated, functional resources. Here we present a publicly accessible, curated, and functional resource, termed "nano-org", containing SMLM data representing the nanoscale distributions of proteins in cells. Nano-org is searchable by comparing the statistical similarity of the datasets it contains. This unique functionality allows the resource to be used to understand the relationships of nanoscale architectures between proteins, cell types or conditions, supporting the development of the field of spatial nano-omics.

Authors

Institutions

Publication Details

Journal
Nature Communications
Published
2025-09-30
DOI
https://doi.org/10.1038/s41467-025-63674-x
Citations
2
Primary Topic
Advanced Fluorescence Microscopy Techniques
Type
article
Field-Weighted Citation Impact
3.27

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Nano-org, a functional resource for single-molecule localisation microscopy data

Patrick Rubin‐Delanchy, Khodor S. Hazime, David J. Williamson, Dylan M. Owen et al.
2 citations
Nature Communications
Advanced Fluorescence Microscopy Techniques
3.27
article

Nano-org, a functional resource for single-molecule localisation microscopy data

Patrick Rubin‐Delanchy, Khodor S. Hazime, David J. Williamson, Dylan M. Owen, Ezra Bruggeman, Daniel M. Davis, Jeremy A. Pike, Ruby Peters, Steven F. Lee, Daniel J. Nieves, A. Garcia, Mohammed Baragilly, Jonathan D. Worboys, Ricardo Henriques, Mahmoud A. Ahmed, S. Shirgill, Kylie Savoye, H. L. Abbott
article en
2 citations

Abstract

The nanoscale organisation of proteins plays a key role in diverse cellular processes, including signalling, adhesion, and structural integrity. Single-molecule localisation microscopy (SMLM) is a super-resolution imaging technique that captures the spatial distributions of proteins in cells with nanometre precision, enabling detailed studies of protein clustering and architecture. However, comparing such data across experiments remains challenging due to a lack of curated, functional resources. Here we present a publicly accessible, curated, and functional resource, termed "nano-org", containing SMLM data representing the nanoscale distributions of proteins in cells. Nano-org is searchable by comparing the statistical similarity of the datasets it contains. This unique functionality allows the resource to be used to understand the relationships of nanoscale architectures between proteins, cell types or conditions, supporting the development of the field of spatial nano-omics.

Nature CommunicationsVol. 16(1)
Birmingham City University (GB), King's College London (GB), University of Exeter (GB), University of Cambridge (GB), Manchester Academic Health Science Centre (GB), University of Manchester (GB), MRC Laboratory for Molecular Cell Biology (GB), Centre for Inflammation Research (GB), University College London (GB), Imperial College London (GB), University of Birmingham (GB), Universidade Nova de Lisboa (PT), Helwan University (EG), University of Sheffield (GB), University of Edinburgh (GB)
European Commission, University of Birmingham, Directorate for Biological Sciences, HORIZON EUROPE Framework Programme, Medical Research Council, Biotechnology and Biological Sciences Research Council
Openalex Percentile: Top 7%
Advanced Fluorescence Microscopy Techniques
3.27
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.