MultiSpaceNet: graph-based joint representation learning for paired spatial transcriptome–proteome data

doi:10.1093/bioinformatics/btag676

2026-09-25

DOI：10.1093/bioinformatics/btag676

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摘要

En 中文

配对空间分析方法现可在同一组织切片上测量转录组与蛋白质组。现有整合方法在起始阶段便做出结构选择：每种模态采用独立图、早期融合将测得的蛋白质嵌入其中使其无法再被预测，或通过交集规则舍弃大部分相似性边。每种选择都限制了后续训练模型的功能。

期刊

Bioinformatics

IF:

5.4

论文数:

1.3K

被引数:

17.9W

机构

Harbin Institute of Technology

学者数:

4.5K

论文数: 1.3K

被引数: 0

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