ArticleMolecular therapy. Nucleic acids2020
Computational Methods and Applications for Identifying Disease-Associated lncRNAs as Potential Biomarkers and Therapeutic Targets.
Article in Molecular therapy. Nucleic acids, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Computational identification and validation of non-coding rna biomarkers in gastrointestinal cancer.Functional & integrative genomics · 2025Review
- The impact of ncRNAs on type 2 diabetes: A comprehensive review covering molecular mechanisms to clinical applications.Molecular therapy. Nucleic acids · 2025Review
- GCN-Based Heterogeneous Complex Feature Learning to Enhance Predictability for LncRNA-Disease Associations.ACS omega · 2024Article
- Multi-Omics Mining of lncRNAs with Biological and Clinical Relevance in Cancer.International journal of molecular sciences · 2023Review
- XGBoost framework with feature selection for the prediction of RNA N5-methylcytosine sites.Molecular therapy : the journal of the American Society of Gene Therapy · 2023Article
- Long non-coding ribonucleic acid urothelial carcinoma-associated 1 promotes high glucose-induced human retinal endothelial cells angiogenesis through regulating micro-ribonucleic acid-624-3p/vascular endothelial growth factor C.Journal of diabetes investigation · 2021Article
- Circulating exosomal miR-363-5p inhibits lymph node metastasis by downregulating PDGFB and serves as a potential noninvasive biomarker for breast cancer.Molecular oncology · 2021Article
- Identification of Rhythmically Expressed LncRNAs in the Zebrafish Pineal Gland and Testis.International journal of molecular sciences · 2021Article
- Knockdown of lncRNA DLEU1 inhibits the tumorigenesis of oral squamous cell carcinoma via regulation of miR‑149‑5p/CDK6 axis.Molecular medicine reports · 2021Article
- Novel lncRNAs Co-Expression Networks Identifies LINC00504 with Oncogenic Role in Luminal A Breast Cancer Cells.International journal of molecular sciences · 2021Article
- Predicting LncRNA-Disease Association by a Random Walk With Restart on Multiplex and Heterogeneous Networks.Frontiers in genetics · 2021Article
- Multi-Omics Data Analyses Construct a Six Immune-Related Genes Prognostic Model for Cervical Cancer in Tumor Microenvironment.Frontiers in genetics · 2021Article
- Integrative Analysis of DNA Methylation Data and Transcriptome Data Identified a DNA Methylation-Dysregulated Four-LncRNA Signature for Predicting Prognosis in Head and Neck Squamous Cell Carcinoma.Frontiers in cell and developmental biology · 2021Article
- Article
- LDNFSGB: prediction of long non-coding rna and disease association using network feature similarity and gradient boosting.BMC bioinformatics · 2020Article
- Transcriptomic Data Analyses Reveal a Reprogramed Lipid Metabolism in HCV-Derived Hepatocellular Cancer.Frontiers in cell and developmental biology · 2020Article
- Characterization of DNA Methylation Patterns and Mining of Epigenetic Markers During Genomic Reprogramming in SCNT Embryos.Frontiers in cell and developmental biology · 2020Article
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7 authors.
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Abstract
Long non-coding RNAs (lncRNAs) have been recognized as critical components of a broad genomic regulatory network and play pivotal roles in physiological and pathological processes. Identification of disease-associated lncRNAs is becoming increasingly crucial for fundamentally improving our understanding of molecular mechanisms of disease and developing novel biomarkers and therapeutic targets. Considering lower efficiency and higher time and labor cost of biological experiments, computer-aided inference of disease-associated RNAs has become a promising avenue for facilitating the study of lncRNA functions and provides complementary value for experimental studies. In this study, we first summarize data and knowledge resources publicly available for the study of lncRNA-disease associations. Then, we present an updated systematic overview of dozens of computational methods and models for inferring lncRNA-disease associations proposed in recent years. Finally, we explore the perspectives and challenges for further studies. Our study provides a guide for biologists and medical scientists to look for dedicated resources and more competent tools for accelerating the unraveling of disease-associated lncRNAs.
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