AWTI-Net Enables Accurate and Interpretable Functional Assessment of Disease-Associated LncRNA Mutations.

CDELDA: A Content-Based Dual-Encoder for Cold-Start lncRNA–Disease Association Prediction

Machine learning approaches for cancer prognosis and diagnosis via non-coding RNA: a comprehensive review

Abstract Non-coding RNAs (ncRNAs), once considered genomic dark matter, are now established as key regulators of gene expression with widespread roles in cellular homeostasis and disease. In cancer, ncRNA expression is frequently and systematically dysregulated, and many of these molecules circulate in stable, protecte...

Computational approaches and data analysis tools for comprehensive non-coding small RNA profiling in liquid biopsies

This thesis demonstrates that the integration of refined isomiR and tRF profiles within targeted liquid biopsy populations (TEPs and PD), supported by advanced bioinformatics tools like miRGalaxy, significantly enhances the accuracy and sensitivity of cancer diagnosis.

Integrative Transcriptomic Network Modeling Coupled with Patient-Derived Validation for Circulating lncRNA Biomarker Discovery in NAFLD: A Comprehensive Workflow.

This chapter offers a comprehensive, reproducible protocol for identifying and clinically validating circulating long noncoding RNA (lncRNA) biomarkers for NAFLD and NASH.

A multi-layer framework for computational cancer epigenomics

A structured multi-layer interpretation framework is proposed that links computational outputs across data-level processing, epigenomics-informed integrative regulatory modeling, and multi-omics-informed clinical interpretation, enabling traceable and mechanistically interpretable clinical inference.

Topology-aware relational learning on heterogeneous networks for lncRNA-disease association prediction.

OBJECTIVE Long non-coding RNAs (lncRNAs) play an irreplaceable role in critical physiological processes such as cell cycle regulation, chromatin remodeling, and tumor suppression, yet traditional wet-lab molecular experiments are expensive and time-consuming. Consequently, there is an urgent need to develop efficient c...