Cooperative integration of spatially resolved multi-omics data with COSMOS
Abstract Recent advancements in biological technologies have enabled the measurement of spatially resolved multi-omics data, yet computational algorithms for this purpose are scarce. Existing tools target either single omics or lack spatial integration. We generate a graph neural network algorithm n...
Saved in:
Main Authors: | Yuansheng Zhou, Xue Xiao, Lei Dong, Chen Tang, Guanghua Xiao, Lin Xu |
---|---|
Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2025-01-01
|
Series: | Nature Communications |
Online Access: | https://doi.org/10.1038/s41467-024-55204-y |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Spatial integration of multi-omics single-cell data with SIMO
by: Penghui Yang, et al.
Published: (2025-02-01) -
Characterizing cell-type spatial relationships across length scales in spatially resolved omics data
by: Rafael dos Santos Peixoto, et al.
Published: (2025-01-01) -
Instantaneous correlations of Shannon’s big data in nonlocal cosmos
by: Igor É. Bulyzhenkov
Published: (2025-01-01) -
Predictive nomogram integrating radiomics and multi‐omics for improved prognosis‐model in cholangiocarcinoma
by: Yunlu Jia, et al.
Published: (2025-01-01) -
Spatially Resolved Multiomics: Data Analysis from Monoomics to Multiomics
by: Changxiang Huan, et al.
Published: (2025-01-01)