AIMC Topic: RNA, Long Noncoding
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Deep learning-based computational approach for predicting ncRNAs-disease associations in metaplastic breast cancer diagnosis.
BMC cancer
May 6, 2025
Non-coding RNAs (ncRNAs) play a crucial role in breast cancer progression, necessitating advanced computational approaches for precise disease classification. This study introduces a Deep Reinforcement Learning (DRL)-based framework for predicting nc...
A divide-and-conquer approach based on deep learning for long RNA secondary structure prediction: Focus on pseudoknots identification.
PloS one
Apr 25, 2025
The accurate prediction of RNA secondary structure, and pseudoknots in particular, is of great importance in understanding the functions of RNAs since they give insights into their folding in three-dimensional space. However, existing approaches ofte...
Machine learning-based identification of cuproptosis-related lncRNA biomarkers in diffuse large B-cell lymphoma.
Cell biology and toxicology
Apr 21, 2025
Multiple machine learning techniques were employed to identify key long non-coding RNA (lncRNA) biomarkers associated with cuproptosis in Diffuse Large B-Cell Lymphoma (DLBCL). Data from the TCGA and GEO databases facilitated the identification of 12...
LMFE: A Novel Method for Predicting Plant LncRNA Based on Multi-Feature Fusion and Ensemble Learning.
Genes
Mar 31, 2025
: Long non-coding RNAs (lncRNAs) play a crucial regulatory role in plant trait expression and disease management, making their accurate prediction a key research focus for guiding biological experiments. While extensive studies have been conducted on...
Multitask learning model for predicting non-coding RNA-disease associations: Incorporating local and global context.
Methods (San Diego, Calif.)
Mar 18, 2025
Long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) are crucial non-coding RNAs involved in various diseases. Understanding these interactions is vital for advancing diagnostic, preventive, and therapeutic strategies. Existing computational methods...
Circulating lncRNAs as biomarkers for severe dengue using a machine learning approach.
The Journal of infection
Mar 14, 2025
OBJECTIVES: Dengue virus (DENV) infection is a significant global health concern, causing severe morbidity and mortality. While many cases present as a mild febrile illness, some progress to life-threatening severe dengue (SD). Early intervention is ...
EVlncRNA-net: A dual-channel deep learning approach for accurate prediction of experimentally validated lncRNAs.
International journal of biological macromolecules
Mar 6, 2025
Long non-coding RNAs (lncRNAs) play key roles in numerous biological processes and are associated with various human diseases. High-throughput RNA sequencing (HTlncRNAs) has identified tens of thousands of lncRNAs across species, but only a small fra...
Big data analysis and machine learning of the role of cuproptosis-related long non-coding RNAs (CuLncs) in the prognosis and immune landscape of ovarian cancer.
Frontiers in immunology
Feb 25, 2025
BACKGROUND: Ovarian cancer (OC) is a severe malignant tumor with a significant threat to women's health, characterized by a high mortality rate and poor prognosis despite conventional treatments such as cytoreductive surgery and platinum-based chemot...
An ensemble deep learning framework for multi-class LncRNA subcellular localization with innovative encoding strategy.
BMC biology
Feb 21, 2025
BACKGROUND: Long non-coding RNA (LncRNA) play pivotal roles in various cellular processes, and elucidating their subcellular localization can offer crucial insights into their functional significance. Accurate prediction of lncRNA subcellular localiz...
Integrating multiomics analysis and machine learning to refine the molecular subtyping and prognostic analysis of stomach adenocarcinoma.
Scientific reports
Jan 30, 2025
Stomach adenocarcinoma (STAD) is a common malignancy with high heterogeneity and a lack of highly precise treatment options. We downloaded the multiomics data of STAD patients in The Cancer Genome Atlas (TCGA)-STAD cohort, which included mRNA, microR...
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