AIMC Topic: RNA, Long Noncoding
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Representation of non-coding RNA-mediated regulation of gene expression using the Gene Ontology.
RNA biology
Oct 7, 2024
Regulatory non-coding RNAs (ncRNAs) are increasingly recognized as integral to the control of biological processes. This is often through the targeted regulation of mRNA expression, but this is by no means the only mechanism through which regulatory ...
Machine learning predicts cuproptosis-related lncRNAs and survival in glioma patients.
Scientific reports
Sep 27, 2024
Gliomas are the most common tumor in the central nervous system in adults, with glioblastoma (GBM) representing the most malignant form, while low-grade glioma (LGG) is a less severe. The prognosis for glioma remains poor even after various treatment...
Identification of immune-related biomarkers for intracerebral hemorrhage diagnosis based on RNA sequencing and machine learning.
Frontiers in immunology
Aug 30, 2024
BACKGROUND: Intracerebral hemorrhage (ICH) is a severe stroke subtype with high morbidity, disability, and mortality rates. Currently, no biomarkers for ICH are available for use in clinical practice. We aimed to explore the roles of RNAs in ICH path...
CRISPR-Enhanced Photocurrent Polarity Switching for Dual-lncRNA Detection Combining Deep Learning for Cancer Diagnosis.
Analytical chemistry
Aug 2, 2024
Abnormal expression in long noncoding RNAs (lncRNAs) is closely associated with cancers. Herein, a novel CRISPR/Cas13a-enhanced photocurrent-polarity-switching photoelectrochemical (PEC) biosensor was engineered for the joint detection of dual lncRNA...
Exploring the roles of RNAs in chromatin architecture using deep learning.
Nature communications
Jul 29, 2024
Recent studies have highlighted the impact of both transcription and transcripts on 3D genome organization, particularly its dynamics. Here, we propose a deep learning framework, called AkitaR, that leverages both genome sequences and genome-wide RNA...
Integrative machine learning and neural networks for identifying PANoptosis-related lncRNA molecular subtypes and constructing a predictive model for head and neck squamous cell carcinoma.
European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
Jun 24, 2024
PURPOSE: PANoptosis is considered a novel type of cell death that plays important roles in tumor progression. In this study, we applied machine learning algorithms to explore the relationships between PANoptosis-related lncRNAs (PRLs) and head and ne...
Long non-coding RNAs in biomarking COVID-19: a machine learning-based approach.
Virology journal
Jun 7, 2024
BACKGROUND: The coronavirus pandemic that started in 2019 has caused the highest mortality and morbidity rates worldwide. Data on the role of long non-coding RNAs (lncRNAs) in coronavirus disease 2019 (COVID-19) is scarce. We aimed to elucidate the r...
Developing a prognostic model using machine learning for disulfidptosis related lncRNA in lung adenocarcinoma.
Scientific reports
Jun 7, 2024
Disulfidptosis represents a novel cell death mechanism triggered by disulfide stress, with potential implications for advancements in cancer treatments. Although emerging evidence highlights the critical regulatory roles of long non-coding RNAs (lncR...
Machine learning-based integration develops an immunogenic cell death-derived lncRNA signature for predicting prognosis and immunotherapy response in lung adenocarcinoma.
Scientific reports
May 22, 2024
Accumulating evidence demonstrates that lncRNAs are involved in the regulation of the immune microenvironment and early tumor development. Immunogenic cell death occurs mainly through the release or increase of tumor-associated antigen and tumor-spec...
Development of a long noncoding RNA-based machine learning model to predict COVID-19 in-hospital mortality.
Nature communications
May 20, 2024
Tools for predicting COVID-19 outcomes enable personalized healthcare, potentially easing the disease burden. This collaborative study by 15 institutions across Europe aimed to develop a machine learning model for predicting the risk of in-hospital m...
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