AIMC Topic: Single-Cell Gene Expression Analysis

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scGANSL: Graph Attention Network with Subspace Learning for scRNA-seq Data Clustering.

Journal of chemical information and modeling Jun 5, 2025
Single-cell RNA sequencing (scRNA-seq) has become a crucial technology for analyzing cellular diversity at the single-cell level. Cell clustering is crucial in scRNA-seq data analysis as it accurately identifies distinct cell types and uncovers poten...
Single-Cell Gene Expression Analysis Sequence Analysis, RNA Cluster Analysis Principal Component Analysis Humans Machine Learning Single-Cell Analysis RNA-Seq
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Identification of mitophagy-related biomarkers in severe acute pancreatitis: integration of WGCNA, machine learning algorithms and scRNA-seq.

Frontiers in immunology May 28, 2025
BACKGROUND: Mitophagy is a highly conserved cellular process in eukaryotic cells that selectively clears dysfunctional or damaged mitochondria through autophagy mechanisms to maintain mitochondrial homeostasis. However, the role of mitophagy in the p...
RNA-Seq Gene Regulatory Networks Single-Cell Gene Expression Analysis Mice Computational Biology Disease Models, Animal Pancreatitis Mitophagy Biomarkers Animals Gene Expression Profiling Single-Cell Analysis Humans Machine Learning Algorithms
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scE2EGAE: enhancing single-cell RNA-Seq data analysis through an end-to-end cell-graph-learnable graph autoencoder with differentiable edge sampling.

Biology direct May 27, 2025
BACKGROUND: Single-cell RNA sequencing (scRNA-Seq) technology reveals biological processes and molecular-level genomic information among individual cells. Numerous computational methods, including methods based on graph neural networks (GNNs), have b...
Single-Cell Analysis RNA-Seq Single-Cell Gene Expression Analysis Sequence Analysis, RNA Humans Neural Networks, Computer Software Algorithms Autoencoder
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GRLGRN: graph representation-based learning to infer gene regulatory networks from single-cell RNA-seq data.

BMC bioinformatics Apr 18, 2025
BACKGROUND: A gene regulatory network (GRN) is a graph-level representation that describes the regulatory relationships between transcription factors and target genes in cells. The reconstruction of GRNs can help investigate cellular dynamics, drug d...
Computational Biology Sequence Analysis, RNA Single-Cell Analysis RNA-Seq Gene Regulatory Networks Single-Cell Gene Expression Analysis Humans Machine Learning Algorithms Deep Learning
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Molecular features and diagnostic modeling of synovium- and IPFP-derived OA macrophages in the inflammatory microenvironment via scRNA-seq and machine learning.

Journal of orthopaedic surgery and research Apr 17, 2025
BACKGROUND: Osteoarthritis (OA) is the leading cause of degenerative joint disease, with total joint replacement as the only definitive cure. However, no disease-modifying therapy is currently available. Inflammation and fibrosis in the infrapatellar...
Humans Machine Learning Macrophages Female Animals Male Adipose Tissue Osteoarthritis Cellular Microenvironment Rats Inflammation Synovial Membrane Rats, Sprague-Dawley Middle Aged Single-Cell Analysis RNA-Seq Single-Cell Gene Expression 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 ...
Nomograms Cell Proliferation Carcinogenesis Vimentin Lysine Single-Cell Gene Expression Analysis Computational Biology Sequence Analysis, RNA Gene Expression Regulation, Neoplastic Cell Line, Tumor Single-Cell Analysis RNA-Seq Gene Regulatory Networks Humans Machine Learning Prognosis Stomach Neoplasms Biomarkers, Tumor
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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...
Computational Biology Sequence Analysis, RNA Cluster Analysis Autoencoder Deep Learning Single-Cell Analysis RNA-Seq Single-Cell Gene Expression Analysis Humans Software Algorithms
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scCorrect: Cross-modality label transfer from scRNA-seq to scATAC-seq using domain adaptation.

Analytical biochemistry Mar 27, 2025
Cell type annotation in single-cell chromatin accessibility sequencing (scATAC-seq) is crucial for enabling researchers to identify subpopulations of cells associated with specific diseases, elucidate gene regulatory networks, and discover markers in...
RNA-Seq Single-Cell Gene Expression Analysis Sequence Analysis, RNA Chromatin Humans Neural Networks, Computer Algorithms Single-Cell Analysis
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Development of a MVI associated HCC prognostic model through single cell transcriptomic analysis and 101 machine learning algorithms.

Scientific reports Mar 7, 2025
Hepatocellular carcinoma (HCC) is an exceedingly aggressive form of cancer that often carries a poor prognosis, especially when it is complicated by the presence of microvascular invasion (MVI). Identifying patients at high risk of MVI is crucial for...
Microvessels Immune Checkpoint Proteins Meta-Analysis as Topic Mutation Datasets as Topic Kaplan-Meier Estimate Liver Neoplasms Carcinoma, Hepatocellular Single-Cell Gene Expression Analysis Immunotherapy Gene Expression Regulation, Neoplastic Treatment Outcome Neoplasm Invasiveness Liver Prognosis Humans Clinical Decision-Making Machine Learning Biomarkers, Tumor Precision Medicine Risk Assessment
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Investigation of cell development and tissue structure network based on natural Language processing of scRNA-seq data.

Journal of translational medicine Mar 4, 2025
BACKGROUND: Single-cell multi-omics technologies, particularly single-cell RNA sequencing (scRNA-seq), have revolutionized our understanding of cellular heterogeneity and development by providing insights into gene expression at the single-cell level...
Humans Animals Sequence Analysis, RNA Natural Language Processing Cell Differentiation Organ Specificity Single-Cell Analysis RNA-Seq Gene Regulatory Networks Single-Cell Gene Expression Analysis
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