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Article

ACLNDA: an asymmetric graph contrastive learning framework for predicting noncoding RNA-disease associations in heterogeneous graphs.

Briefings in bioinformatics - 23 Sept 2024

Fu Laiyi, Yao ZhiYuan, Zhou Yangyi, Peng Qinke, Lyu Hongqiang

Abstract excerpt

Noncoding RNAs (ncRNAs), including long noncoding RNAs (lncRNAs) and microRNAs (miRNAs), play crucial roles in gene expression regulation and are significant in disease associations and medical research. Accurate ncRNA-disease association prediction is essential for understanding disease mechanisms and developing treatments. Existing methods often focus on single tasks like lncRNA-disease associations (LDAs),...

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Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

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PMID: 39441244
DOI: 10.1093/bib/bbae533
PMCID: PMC11497849

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