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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
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...

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
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...

Evolutionary learning-derived lncRNA signature with biomarker discovery for predicting stage of colon adenocarcinoma.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
In recent years, long non-coding RNAs (lncRNAs) have emerged as potential regulators of biological processes and genes, with the potential to serve as valuable biomarkers for cancer diagnosis and prognosis prediction. This work proposes an evolutiona...

Introducing TEC-LncMir for prediction of lncRNA-miRNA interactions through deep learning of RNA sequences.

Briefings in bioinformatics
The interactions between long noncoding RNA (lncRNA) and microRNA (miRNA) play critical roles in life processes, highlighting the necessity to enhance the performance of state-of-the-art models. Here, we introduced TEC-LncMir, a novel approach for pr...

[Screening of characteristic genes of salivary gland adenoid cystic carcinoma based on weighted co-expression network and machine learning].

Shanghai kou qiang yi xue = Shanghai journal of stomatology
PURPOSE: To identify potential biomarkers of salivary gland adenoid cystic carcinoma to further understand the potential pathogenesis of adenoid cystic carcinoma.

Bidirectional recurrent neural network approach for predicting cervical cancer recurrence and survival.

Scientific reports
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...

Integrating multiomics analysis and machine learning to refine the molecular subtyping and prognostic analysis of stomach adenocarcinoma.

Scientific reports
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...

Transcriptomic profiling and machine learning reveal novel RNA signatures for enhanced molecular characterization of Hashimoto's thyroiditis.

Scientific reports
While ultrasonography effectively diagnoses Hashimoto's thyroiditis (HT), exploring its transcriptomic landscape could reveal valuable insights into disease mechanisms. This study aimed to identify HT-associated RNA signatures and investigate their p...

An ensemble learning method combined with multiple feature representation strategies to predict lncRNA subcellular localizations.

Computational biology and chemistry
Long non-coding RNAs (lncRNAs) are strongly associated with cellular physiological mechanisms and implicated in the numerous diseases. By exploring the subcellular localizations of lncRNAs, we can not only gain crucial insights into the molecular mec...

An ensemble deep learning framework for multi-class LncRNA subcellular localization with innovative encoding strategy.

BMC biology
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...