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Single-Cell Gene Expression Analysis

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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 39723205
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 ...
Algorithms Animals Aortic Aneurysm, Abdominal Biomarkers Computational Biology Disease Models, Animal Ferroptosis Gene Expression Profiling Humans Machine Learning Male Mice Proto-Oncogene Proteins c-pim-1 RNA-Seq Single-Cell Gene Expression Analysis
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Robust self-supervised learning strategy to tackle the inherent sparsity in single-cell RNA-seq data.

Briefings in bioinformatics 39550222
Single-cell RNA sequencing (scRNA-seq) is a powerful tool for elucidating cellular heterogeneity and tissue function in various biological contexts. However, the sparsity in scRNA-seq data limits the accuracy of cell type annotation and transcriptomi...
Algorithms Computational Biology Gene Expression Profiling Humans RNA-Seq Sequence Analysis, RNA Single-Cell Analysis Single-Cell Gene Expression Analysis Supervised Machine Learning
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scDTL: enhancing single-cell RNA-seq imputation through deep transfer learning with bulk cell information.

Briefings in bioinformatics 39504481
The increasing single-cell RNA sequencing (scRNA-seq) data enable researchers to explore cellular heterogeneity and gene expression profiles, offering a high-resolution view of the transcriptome at the single-cell level. However, the dropout events, ...
Algorithms Computational Biology Deep Learning Gene Expression Profiling Humans RNA-Seq Sequence Analysis, RNA Single-Cell Analysis Single-Cell Gene Expression Analysis Transcriptome
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Structure-preserved integration of scRNA-seq data using heterogeneous graph neural network.

Briefings in bioinformatics 39446194
The integration of single-cell RNA sequencing (scRNA-seq) data from multiple experimental batches enables more comprehensive characterizations of cell states. Given that existing methods disregard the structural information between cells and genes, w...
Algorithms Animals Computational Biology Humans Neural Networks, Computer RNA-Seq Sequence Analysis, RNA Single-Cell Analysis Single-Cell Gene Expression Analysis
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Impact of Mitophagy-Related Genes on the Diagnosis and Development of Esophageal Squamous Cell Carcinoma via Single-Cell RNA-seq Analysis and Machine Learning Algorithms.

Journal of microbiology and biotechnology 39344350
As a treatment for esophageal squamous cell carcinoma (ESCC), which is common and fatal, mitophagy is a conserved cellular mechanism that selectively removes damaged mitochondria and is crucial for cellular homeostasis. While tumor development and re...
Algorithms Apoptosis Regulatory Proteins Biomarkers, Tumor Cell Line, Tumor Cell Movement Cell Proliferation Esophageal Neoplasms Esophageal Squamous Cell Carcinoma Gene Expression Regulation, Neoplastic Humans Machine Learning Mitochondria Mitochondrial Proteins Mitophagy Prognosis RNA-Seq Single-Cell Analysis Single-Cell Gene Expression Analysis Transcriptome
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Integrating large-scale single-cell RNA sequencing in central nervous system disease using self-supervised contrastive learning.

Communications biology 39251817
The central nervous system (CNS) comprises a diverse range of brain cell types with distinct functions and gene expression profiles. Although single-cell RNA sequencing (scRNA-seq) provides new insights into the brain cell atlases, integrating large-...
Animals Atlases as Topic Central Nervous System Cluster Analysis Datasets as Topic Deep Learning Humans Neurodegenerative Diseases Single-Cell Gene Expression Analysis Supervised Machine Learning
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scRGCL: a cell type annotation method for single-cell RNA-seq data using residual graph convolutional neural network with contrastive learning.

Briefings in bioinformatics 39708840
Cell type annotation is a critical step in analyzing single-cell RNA sequencing (scRNA-seq) data. A large number of deep learning (DL)-based methods have been proposed to annotate cell types of scRNA-seq data and have achieved impressive results. How...
Algorithms Animals Computational Biology Deep Learning Humans Mice Neural Networks, Computer RNA-Seq Sequence Analysis, RNA Single-Cell Analysis Single-Cell Gene Expression Analysis Software
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Integrating single-cell RNA-Seq and machine learning to dissect tryptophan metabolism in ulcerative colitis.

Journal of translational medicine 39707393
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...
Algorithms Colitis, Ulcerative Humans Machine Learning RNA-Seq Single-Cell Analysis Single-Cell Gene Expression Analysis Tryptophan
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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 39481313
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...
Acute Lung Injury Animals Biomarkers Computational Biology Disease Progression Gene Expression Profiling Humans Machine Learning Male Mice RNA-Seq Sepsis Single-Cell Analysis Single-Cell Gene Expression Analysis Transcriptome
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CSI-GEP: A GPU-based unsupervised machine learning approach for recovering gene expression programs in atlas-scale single-cell RNA-seq data.

Cell genomics 39788105
Exploratory analysis of single-cell RNA sequencing (scRNA-seq) typically relies on hard clustering over two-dimensional projections like uniform manifold approximation and projection (UMAP). However, such methods can severely distort the data and hav...
Animals Brain Gene Expression Profiling Humans Mice RNA-Seq Sequence Analysis, RNA Single-Cell Analysis Single-Cell Gene Expression Analysis Unsupervised Machine Learning
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