ArticleJournal of oral biology and craniofacial research
Enhanced hierarchical attention networks for predictive interactome analysis of LncRNA and CircRNA in oral herpes virus.
Article in Journal of oral biology and craniofacial research. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- AWTI-Net Enables Accurate and Interpretable Functional Assessment of Disease-Associated LncRNA Mutations.Interdisciplinary sciences, computational life sciences · 2026Article
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2 authors.
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Abstract
Background: Non-coding RNAs, including lncRNAs, circRNAs, and microRNAs, constitute 98 % of the human transcriptome and are vital regulators of gene expression, cellular processes, and host-pathogen interactions, particularly in viral infections. This study explores lncRNA-circRNA interactions and their biological significance in oral viral infections. Methods: ViRBase, a database with over 820,000 interactions involving 50,000 RNAs from 116 viruses and 36 host organisms, was used to analyze herpesvirus datasets. The study employed hierarchical attention and knowledge graph embeddings to represent nodes and edges in the knowledge graph. These served as input features for a hierarchical attention model trained over 100 epochs. Model performance was evaluated based on loss calculation, optimization, and attention weight stability. Results: The model achieved a final loss of 0.000180 at Epoch 100, with stable attention weights confirming reliability. Node embedding statistics showed a mean of 0.005110 and a standard deviation of 0.013370, while attention weights had a high mean of 0.997178, emphasizing model robustness. Conclusion: This study provides insights into lncRNA-circRNA interactions in herpes viral infections, enhancing therapeutic development, disease progression monitoring, and understanding host-pathogen interactions, paving the way for targeted interventions and improved outcomes.
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