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Article

iGATTLDA: Integrative graph attention and transformer-based model for predicting lncRNA-Disease associations.

IET systems biology - 1 Oct 2024

Momanyi Biffon Manyura, Temesgen Sebu Aboma, Wang Tian-Yu, Gao Hui, Gao Ru, Tang Hua, Tang Li-Xia

Abstract excerpt

Long non-coding RNAs (lncRNAs) have emerged as significant contributors to the regulation of various biological processes, and their dysregulation has been linked to a variety of human disorders. Accurate prediction of potential correlations between lncRNAs and diseases is crucial for advancing disease diagnostics and treatment procedures. The authors introduced a novel computational method, iGATTLDA, for the...

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PMID: 39308027
DOI: 10.1049/syb2.12098
PMCID: PMC11490194

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