AIMC Topic: RNA, Long Noncoding
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Identifying the NEAT1/miR-26b-5p/S100A2 axis as a regulator in Parkinson's disease based on the ferroptosis-related genes.
PloS one
Dec 31, 2024
OBJECTIVES: Parkinson's disease (PD) is a complex neurodegenerative disease with unclear pathogenesis. Some recent studies have shown that there is a close relationship between PD and ferroptosis. We aimed to identify the ferroptosis-related genes (F...
Bidirectional recurrent neural network approach for predicting cervical cancer recurrence and survival.
Scientific reports
Dec 30, 2024
Cervical cancer is a deadly disease in women globally. There is a greater chance of getting rid of cervical cancer in case of earliest diagnosis. But for some patients, there is a chance of recurrence. The chances of treating the Recurrence of cervic...
Predicting lncRNA-protein interactions using a hybrid deep learning model with dinucleotide-codon fusion feature encoding.
BMC genomics
Dec 28, 2024
Long non-coding RNAs (lncRNAs) play crucial roles in numerous biological processes and are involved in complex human diseases through interactions with proteins. Accurate identification of lncRNA-protein interactions (LPI) can help elucidate the func...
BiGM-lncLoc: Bi-level Multi-Graph Meta-Learning for Predicting Cell-Specific Long Noncoding RNAs Subcellular Localization.
Interdisciplinary sciences, computational life sciences
Dec 26, 2024
The precise spatiotemporal expression of long noncoding RNAs (lncRNAs) plays a pivotal role in biological regulation, and aberrant expression of lncRNAs in different subcellular localizations has been intricately linked to the onset and progression o...
Analysis of the basement membrane-related genes ITGA7 and its regulatory role in periodontitis via machine learning: a retrospective study.
BMC oral health
Dec 24, 2024
BACKGROUND: Periodontitis is among the most prevalent inflammatory conditions and greatly impacts oral health. This study aimed to elucidate the role of basement membrane-related genes in the pathogenesis and diagnosis of periodontitis.
Machine learning-based integration develops a disulfidptosis-related lncRNA signature for improving outcomes in gastric cancer.
Artificial cells, nanomedicine, and biotechnology
Dec 19, 2024
Gastric cancer remains one of the deadliest cancers globally due to delayed detection and limited treatment options, underscoring the critical need for innovative prognostic methods. Disulfidptosis, a recently discovered programmed cell death trigger...
Integrating bioinformatics and machine learning to uncover lncRNA LINC00269 as a key regulator in Parkinson's disease via pyroptosis pathways.
European journal of medical research
Dec 18, 2024
BACKGROUND: Pyroptosis, a specific type of programmed cell death, which has become a significant factor to Parkinson's disease (PD). Concurrently, long non-coding RNAs (lncRNAs) have garnered attention for their regulatory roles in neurodegenerative ...
The significance of long chain non-coding RNA signature genes in the diagnosis and management of sepsis patients, and the development of a prediction model.
Frontiers in immunology
Dec 12, 2024
BACKGROUND: Sepsis is a life-threatening organ dysfunction condition produced by dysregulation of the host response to infection. It is now characterized by a high clinical morbidity and mortality rate, endangering patients' lives and health. The pur...
Analysis of four long non-coding RNAs for hepatocellular carcinoma screening and prognosis by the aid of machine learning techniques.
Scientific reports
Nov 28, 2024
Hepatocellular carcinoma (HCC) represents a significant health burden in Egypt, largely attributable to the endemic prevalence of hepatitis B and C viruses. Early identification of HCC remains a challenge due to the lack of widespread screening among...
Plant lncRNA-miRNA Interaction Prediction Based on Counterfactual Heterogeneous Graph Attention Network.
Interdisciplinary sciences, computational life sciences
Oct 9, 2024
Identifying interactions between long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) provides a new perspective for understanding regulatory relationships in plant life processes. Recently, computational methods based on graph neural networks (GNNs...
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