AIMC Topic: Single-Cell Analysis

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Comprehensive analysis of scRNA-seq and bulk RNA-seq data via machine learning and bioinformatics reveals the role of lysine metabolism-related genes in gastric carcinogenesis.

BMC cancer Apr 9, 2025
BACKGROUND: Gastric cancer (GC) is a highly aggressive and heterogeneous cancer with extremely complex biological characteristics. Lysine and its metabolism are closely related to human cancer, but little is known about how lysine metabolism-related ...
Single-Cell Analysis RNA-Seq Gene Regulatory Networks Single-Cell Gene Expression Analysis Stomach Neoplasms Biomarkers, Tumor Humans Cell Line, Tumor Machine Learning Cell Proliferation Prognosis Carcinogenesis Computational Biology Vimentin Sequence Analysis, RNA Lysine Gene Expression Regulation, Neoplastic Nomograms
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Unique and shared transcriptomic signatures underlying localized scleroderma pathogenesis identified using interpretable machine learning.

JCI insight Apr 8, 2025
Using transcriptomic profiling at single-cell resolution, we investigated cell-intrinsic and cell-extrinsic signatures associated with pathogenesis and inflammation-driven fibrosis in both adult and pediatric patients with localized scleroderma (LS)....
Humans Machine Learning Female Adult Male RNA-Seq Scleroderma, Systemic Scleroderma, Localized Case-Control Studies Middle Aged Adolescent Gene Expression Profiling Child Transcriptome Single-Cell Analysis
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CNRein: an evolution-aware deep reinforcement learning algorithm for single-cell DNA copy number calling.

Genome biology Apr 7, 2025
Low-pass single-cell DNA sequencing technologies and algorithmic advancements have enabled haplotype-specific copy number calling on thousands of cells within tumors. However, measurement uncertainty may result in spurious CNAs inconsistent with real...
DNA Copy Number Variations Ovarian Neoplasms Reinforcement Machine Learning Breast Neoplasms Deep Learning Single-Cell Analysis Sequence Analysis, DNA Humans Algorithms Female
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scAMZI: attention-based deep autoencoder with zero-inflated layer for clustering scRNA-seq data.

BMC genomics Apr 7, 2025
BACKGROUND: Clustering scRNA-seq data plays a vital role in scRNA-seq data analysis and downstream analyses. Many computational methods have been proposed and achieved remarkable results. However, there are several limitations of these methods. First...
Sequence Analysis, RNA Cluster Analysis Autoencoder RNA-Seq Single-Cell Gene Expression Analysis Computational Biology Humans Software Algorithms Deep Learning Single-Cell Analysis
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Large-scale bulk and single-cell RNA sequencing combined with machine learning reveals glioblastoma-associated neutrophil heterogeneity and establishes a VEGFA neutrophil prognostic model.

Biology direct Apr 5, 2025
BACKGROUND: Neutrophils play a key role in the tumor microenvironment (TME); however, their functions in glioblastoma (GBM) are overlooked and insufficiently studied. A detailed analysis of GBM-associated neutrophil (GBMAN) subpopulations may offer n...
Vascular Endothelial Growth Factor A Machine Learning Prognosis Tumor Microenvironment Brain Neoplasms Single-Cell Analysis Sequence Analysis, RNA Neutrophils Glioblastoma Humans
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101 Machine Learning Algorithms for Mining Esophageal Squamous Cell Carcinoma Neoantigen Prognostic Models in Single-Cell Data.

International journal of molecular sciences Apr 4, 2025
Esophageal squamous cell carcinoma (ESCC) is one of the most aggressive malignant tumors in the digestive tract, characterized by a high recurrence rate and inadequate immunotherapy options. We analyzed mutation data of ESCC from public databases and...
Mutation Esophageal Neoplasms Data Mining Esophageal Squamous Cell Carcinoma Prognosis Humans Tumor Microenvironment Machine Learning Single-Cell Analysis Algorithms Antigens, Neoplasm
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MIST: An interpretable and flexible deep learning framework for single-T cell transcriptome and receptor analysis.

Science advances Apr 4, 2025
Joint analysis of transcriptomic and T cell receptor (TCR) features at single-cell resolution provides a powerful approach for in-depth T cell immune function research. Here, we introduce a deep learning framework for single-T cell transcriptome and ...
SARS-CoV-2 T-Lymphocytes Gene Expression Profiling Transcriptome Humans COVID-19 Immunotherapy CD8-Positive T-Lymphocytes Chemokine CXCL13 Deep Learning Single-Cell Analysis Lung Neoplasms Receptors, Antigen, T-Cell
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Mitigating ambient RNA and doublets effects on single cell transcriptomics analysis in cancer research.

Cancer letters Apr 3, 2025
In cancer biology, where understanding the tumor microenvironment at high resolution is vital, ambient RNA contamination becomes a considerable problem. This hinders accurate delineation of intratumoral heterogeneity, complicates the identification o...
Humans Tumor Microenvironment Single-Cell Analysis RNA-Seq Computational Biology Gene Expression Regulation, Neoplastic Biomarkers, Tumor Neoplasms Gene Expression Profiling Transcriptome
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Predicting cell cycle stage from 3D single-cell nuclear-stained images.

Life science alliance Apr 3, 2025
The cell cycle governs the proliferation of all eukaryotic cells. Profiling cell cycle dynamics is therefore central to basic and biomedical research. However, current approaches to cell cycle profiling involve complex interventions that may confound...
Cell Nucleus Cell Cycle Image Processing, Computer-Assisted Support Vector Machine Microscopy, Fluorescence Humans Neural Networks, Computer Machine Learning Single-Cell Analysis Imaging, Three-Dimensional
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Integrating single-cell RNA sequencing, WGCNA, and machine learning to identify key biomarkers in hepatocellular carcinoma.

Scientific reports Apr 1, 2025
The microarray and single-cell RNA-sequencing (scRNA-seq) datasets of hepatocellular carcinoma (HCC) were downloaded from the Gene Expression Omnibus (GEO) database. Differential expression analysis and weighted gene co-expression network analysis (W...
Humans Gene Regulatory Networks Sequence Analysis, RNA Gene Expression Regulation, Neoplastic Gene Expression Profiling Machine Learning Biomarkers, Tumor Liver Neoplasms Molecular Docking Simulation Carcinoma, Hepatocellular Single-Cell Analysis
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