Contrastive Learning-Based Method for Single-Cell Multi-omics Data Clustering

doi:10.1007/978-981-95-0698-9_29

2026-01-01

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DOI：10.1007/978-981-95-0698-9_29

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单细胞多组学数据聚类的对比学习方法scCLC：基于对比学习的单细胞多组学数据聚类方法scCLC，通过对比学习框架整合单细胞RNA测序数据和单细胞ATAC测序数据，采用专门的数据增强策略和自监督学习模型进行细胞表征学习。该方法利用单细胞多组学数据拓扑结构确定正样本对，不仅增大训练样本量，还为模型提供基础标签先验以学习更利于聚类的细胞表征。在单细胞多组学数据集上的实验结果表明，scCLC具有优异的聚类性能；应用于可视化时，能有效区分细胞亚型。

Keyword:

Single-cell Multi-omics

Cell Heterogeneity

Self-supervised Learning

期刊

BIOINFORMATICS RESEARCH AND APPLICATIONS, ISBRA 2025, PT I

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central south university

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2.2W

论文数: 6.3K

被引数: 3

university of calgary

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6.1K

论文数: 2.6K

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