AIMC Topic: RNA-Seq

Clear Filters Showing 41 to 50 of 202 articles

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 Diabetes Mellitus, Type 2 Single-Cell Gene Expression Analysis Humans Single-Cell Analysis Protein Interaction Maps Machine Learning Ion Transport Gene Expression Profiling
View on PubMed DOI

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 Biomarkers Mustard Gas Humans Chemical Warfare Agents Male Machine Learning Gene Expression Profiling Algorithms RNA-Seq
View on PubMed DOI

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...
Cellular Senescence Sequence Analysis, RNA Fibroblasts Skin Humans Machine Learning Transcriptome Single-Cell Analysis RNA-Seq
View on PubMed DOI

Whole Blood vs Serum-Derived Exosomes for Host and Pathogen-Specific Tuberculosis Biomarker Identification: RNA-Seq-Based Machine-Learning Approach.

Biochemical genetics Dec 23, 2024
Mycobacterium tuberculosis (Mtb) remains a leading infectious disease responsible for millions of deaths. RNA sequencing is a rapidly growing technique and a powerful approach to understanding host and pathogen cross-talks via transcriptional respons...
Humans Machine Learning Biomarkers Exosomes Tuberculosis Mycobacterium tuberculosis Host-Pathogen Interactions Female Male Gene Expression Profiling RNA-Seq
View on PubMed DOI

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...
RNA-Seq Single-Cell Gene Expression Analysis Colitis, Ulcerative Tryptophan Humans Machine Learning Algorithms Single-Cell Analysis
View on PubMed DOI

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 ...
Gene Expression Profiling RNA-Seq Single-Cell Gene Expression Analysis Mice Biomarkers Humans Proto-Oncogene Proteins c-pim-1 Animals Machine Learning Computational Biology Male Algorithms Disease Models, Animal Ferroptosis Aortic Aneurysm, Abdominal
View on PubMed DOI

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...
CD4-Positive T-Lymphocytes Humans Gene Expression Regulation Diabetic Retinopathy Molecular Targeted Therapy Gene Regulatory Networks Biomarkers Fatty Acid Synthase, Type I Memory T Cells Nomograms Machine Learning Phospholipid Transfer Proteins ROC Curve Human Umbilical Vein Endothelial Cells Regulated Cell Death Random Forest RNA-Seq
View on PubMed DOI

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...
RNA-Seq Gene Expression Regulation, Neoplastic Receptors, G-Protein-Coupled Glioblastoma Gene Expression Profiling Transcriptome Deep Learning Humans Prognosis Female Survival Rate Biomarkers, Tumor Brain Neoplasms Male Middle Aged
View on PubMed DOI

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 RNA-Seq Sequence Analysis, RNA Gene Expression Regulation, Neoplastic Transcriptome Tumor Microenvironment Deep Learning Neoplasms Cell Line, Tumor Gene Expression Profiling Single-Cell Analysis
View on PubMed DOI

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...
RNA-Seq Mice Computational Biology Multiple Myeloma Transcriptome Case-Control Studies Single-Cell Analysis Machine Learning Humans Blood-Brain Barrier Animals Gene Expression Profiling
View on PubMed DOI
Popular Topics
Recent Journals