Identifying spatial domains from spatial multi-omics data using consistent and specific deep subspace learning

Guangchang Cai

doi:10.1016/j.inffus.2025.103428

Identifying spatial domains from spatial multi-omics data using consistent and specific deep subspace learning

2025-06-27

0

PRE

AI

DOI：10.1016/j.inffus.2025.103428

Original

Original request for help

Save

Abstract

En 中文

• A deep subspace learning model is proposed for spatial domain identification. • Our model captures local features and uses self-expression to learn global affinities. • The consistent and complementary cross-omics information is effectively extracted. • Dual constraints are introduced to enhance information extraction. • Experiments demonstrate that our model consistently outperforms existing methods.

Keywords:

Spatial multi-omics data

Spatial domain identification

Deep subspace clustering

Multi-view learning

Identifying spatial domains from spatial multi-omics data using consistent and specific deep subspace learning

Abstract

Journal

Organization