AIMC Topic: RNA-Seq

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Deciphering the role of metal ion transport-related genes in T2D pathogenesis and immune cell infiltration via scRNA-seq and machine learning.

Frontiers in immunology Jan 24, 2025
INTRODUCTION: Type 2 diabetes (T2D) is a complex metabolic disorder with significant global health implications. Understanding the molecular mechanisms underlying T2D is crucial for developing effective therapeutic strategies. This study employs sing...
RNA-Seq Gene Regulatory Networks Metals Humans Single-Cell Gene Expression Analysis Machine Learning Diabetes Mellitus, Type 2 Gene Expression Profiling Single-Cell Analysis Protein Interaction Maps Ion Transport
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Identifying candidate RNA-seq biomarkers for severity discrimination in chemical injuries: A machine learning and molecular dynamics approach.

International immunopharmacology Jan 22, 2025
INTRODUCTION: Biomarkers play a crucial role across various fields by providing insights into biological responses to interventions. High-throughput gene expression profiling technologies facilitate the discovery of data-driven biomarkers through ext...
Molecular Dynamics Simulation Humans Mustard Gas Machine Learning Chemical Warfare Agents Biomarkers Algorithms Male Gene Expression Profiling RNA-Seq
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SenPred: a single-cell RNA sequencing-based machine learning pipeline to classify deeply senescent dermal fibroblast cells for the detection of an in vivo senescent cell burden.

Genome medicine Jan 14, 2025
BACKGROUND: Senescence classification is an acknowledged challenge within the field, as markers are cell-type and context dependent. Currently, multiple morphological and immunofluorescence markers are required. However, emerging scRNA-seq datasets h...
Humans Sequence Analysis, RNA Machine Learning Fibroblasts Transcriptome Skin Single-Cell Analysis Cellular Senescence RNA-Seq
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Integrating single-cell RNA-Seq and machine learning to dissect tryptophan metabolism in ulcerative colitis.

Journal of translational medicine Dec 20, 2024
BACKGROUND: Ulcerative colitis (UC) is a persistent inflammatory bowels disease (IBD) characterized by immune response dysregulation and metabolic disruptions. Tryptophan metabolism has been believed as a significant factor in UC pathogenesis, with s...
Humans Machine Learning Algorithms Tryptophan Single-Cell Analysis RNA-Seq Single-Cell Gene Expression Analysis Colitis, Ulcerative
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Integration of bulk/scRNA-seq and multiple machine learning algorithms identifies PIM1 as a biomarker associated with cuproptosis and ferroptosis in abdominal aortic aneurysm.

Frontiers in immunology Dec 11, 2024
BACKGROUND: Abdominal aortic aneurysm (AAA) is a serious life-threatening vascular disease, and its ferroptosis/cuproptosis markers have not yet been characterized. This study was aiming to identify markers associated with ferroptosis/cuproptosis in ...
RNA-Seq Single-Cell Gene Expression Analysis Mice Computational Biology Humans Animals Machine Learning Disease Models, Animal Male Algorithms Gene Expression Profiling Ferroptosis Biomarkers Aortic Aneurysm, Abdominal Proto-Oncogene Proteins c-pim-1
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Integrative analysis of PANoptosis-related genes in diabetic retinopathy: machine learning identification and experimental validation.

Frontiers in immunology Dec 4, 2024
BACKGROUND: Diabetic retinopathy (DR) is a major complication of diabetes, leading to severe vision impairment. Understanding the molecular mechanisms, particularly PANoptosis, underlying DR is crucial for identifying potential biomarkers and therape...
Gene Expression Regulation Molecular Targeted Therapy Memory T Cells Fatty Acid Synthase, Type I Phospholipid Transfer Proteins Regulated Cell Death Nomograms Human Umbilical Vein Endothelial Cells Random Forest CD4-Positive T-Lymphocytes Humans ROC Curve Diabetic Retinopathy RNA-Seq Machine Learning Gene Regulatory Networks Biomarkers
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The G Protein-Coupled Receptor-Related Gene Signatures for Diagnosis and Prognosis in Glioblastoma: A Deep Learning Model Using RNA-Seq Data.

Asian Pacific journal of cancer prevention : APJCP Dec 1, 2024
BACKGROUND: Glioblastoma (GBM) is the most aggressive cancer in the central nervous system in glial cells. Finding novel biomarkers in GBM offers numerous advantages that can contribute to early detection, personalized treatment, improved patient out...
Glioblastoma Deep Learning RNA-Seq Gene Expression Regulation, Neoplastic Receptors, G-Protein-Coupled Female Survival Rate Biomarkers, Tumor Brain Neoplasms Male Middle Aged Gene Expression Profiling Transcriptome Humans Prognosis
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DeSide: A unified deep learning approach for cellular deconvolution of tumor microenvironment.

Proceedings of the National Academy of Sciences of the United States of America Nov 8, 2024
Cellular deconvolution via bulk RNA sequencing (RNA-seq) presents a cost-effective and efficient alternative to experimental methods such as flow cytometry and single-cell RNA-seq (scRNA-seq) for analyzing the complex cellular composition of tumor mi...
Humans Tumor Microenvironment Gene Expression Regulation, Neoplastic Cell Line, Tumor Neoplasms Single-Cell Analysis Gene Expression Profiling RNA-Seq Transcriptome Sequence Analysis, RNA Deep Learning
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HiDDEN: a machine learning method for detection of disease-relevant populations in case-control single-cell transcriptomics data.

Nature communications Nov 2, 2024
In case-control single-cell RNA-seq studies, sample-level labels are transferred onto individual cells, labeling all case cells as affected, when in reality only a small fraction of them may actually be perturbed. Here, using simulations, we demonstr...
Computational Biology Multiple Myeloma Single-Cell Analysis RNA-Seq Humans Mice Machine Learning Blood-Brain Barrier Animals Gene Expression Profiling Transcriptome Case-Control Studies
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Essential blood molecular signature for progression of sepsis-induced acute lung injury: Integrated bioinformatic, single-cell RNA Seq and machine learning analysis.

International journal of biological macromolecules Oct 31, 2024
In this study, we aimed to identify an essential blood molecular signature for chacterizing the progression of sepsis-induced acute lung injury using integrated bioinformatic and machine learning analysis. The results showed that a total of 88 functi...
Humans Machine Learning Biomarkers RNA-Seq Gene Expression Profiling Single-Cell Gene Expression Analysis Acute Lung Injury Transcriptome Mice Animals Sepsis Computational Biology Male Single-Cell Analysis Disease Progression
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