AIMC Topic: Single-Cell Analysis

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Pathway Enrichment-Based Unsupervised Learning Identifies Novel Subtypes of Cancer-Associated Fibroblasts in Pancreatic Ductal Adenocarcinoma.

Interdisciplinary sciences, computational life sciences Jun 1, 2025
Existing single-cell clustering methods are based on gene expressions that are susceptible to dropout events in single-cell RNA sequencing (scRNA-seq) data. To overcome this limitation, we proposed a pathway-based clustering method for single cells (...
Transcriptome Single-Cell Analysis Gene Expression Regulation, Neoplastic Cluster Analysis Humans Gene Expression Profiling Carcinoma, Pancreatic Ductal Cancer-Associated Fibroblasts Unsupervised Machine Learning Pancreatic Neoplasms
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scDMSC: Deep Multi-View Subspace Clustering for Single-Cell Multi-Omics Data.

IEEE journal of biomedical and health informatics Jun 1, 2025
Single-cell multi-omics sequencing technology comprehensively considers various molecular features to reveal the complexity of cells information. The clustering analysis of multi-omics data provides new insight into cellular heterogeneity. However, m...
Unsupervised Machine Learning Transcriptome Humans Algorithms Deep Learning Genomics Multiomics Gene Expression Profiling Single-Cell Analysis Cluster Analysis Computational Biology
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Integrating bulk RNA-seq and scRNA-seq analyses with machine learning to predict platinum response and prognosis in ovarian cancer.

Scientific reports May 31, 2025
Platinum-based therapy is an integral part of the standard treatment for ovarian cancer. However, despite extensive research spanning several decades, the identification of dependable predictive biomarkers for platinum response in clinical practice h...
RNA-Seq Single-Cell Gene Expression Analysis Gene Expression Regulation, Neoplastic Machine Learning Drug Resistance, Neoplasm Prognosis Ovarian Neoplasms Humans Gene Expression Profiling Female Platinum Transcriptome Biomarkers, Tumor Single-Cell Analysis Antineoplastic Agents
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Integration of Bulk RNA and Single-Cell Analyses Reveal Distinct Expression Patterns of Anoikis-Related Genes and the Immunosuppressive Role of NQO1 Macrophages in Hepatocellular Carcinoma.

FASEB journal : official publication of the Federation of American Societies for Experimental Biology May 31, 2025
Anoikis resistance plays a crucial role in the proliferation, metastasis, and invasion of hepatocellular carcinoma (HCC). However, the key genes involved remain to be identified. This study aimed to investigate the prognostic value and impact of anoi...
Prognosis Female Tumor Microenvironment Male Humans Macrophages Single-Cell Analysis Gene Expression Regulation, Neoplastic Anoikis NAD(P)H Dehydrogenase (Quinone) Cell Line, Tumor Liver Neoplasms Carcinoma, Hepatocellular
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Identification of novel therapeutic targets in hepatitis-B virus-associated membranous nephropathy using scRNA-seq and machine learning.

Scientific reports May 29, 2025
Hepatitis B Virus-associated membranous nephropathy (HBV-MN) significantly impacts renal health, particularly in areas with high HBV prevalence. Understanding the molecular mechanisms underlying HBV-MN is crucial for developing effective therapeutic ...
Hepatitis B Single-Cell Analysis RNA-Seq Glomerulonephritis, Membranous Podocytes Single-Cell Gene Expression Analysis MicroRNAs Machine Learning Humans Hepatitis B virus
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scMODAL: a general deep learning framework for comprehensive single-cell multi-omics data alignment with feature links.

Nature communications May 29, 2025
Recent advancements in single-cell technologies have enabled comprehensive characterization of cellular states through transcriptomic, epigenomic, and proteomic profiling at single-cell resolution. These technologies have significantly deepened our u...
Computational Biology Multiomics Epigenomics Transcriptome Proteomics Humans Deep Learning Neural Networks, Computer Single-Cell Analysis Gene Expression Profiling Genomics
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SCIG: Machine learning uncovers cell identity genes in single cells by genetic sequence codes.

Nucleic acids research May 22, 2025
Deciphering cell identity genes is pivotal to understanding cell differentiation, development, and cell identity dysregulation involving diseases. Here, we introduce SCIG, a machine-learning method to uncover cell identity genes in single cells. In a...
Epigenesis, Genetic Transcription Factors Cell Differentiation Gene Expression Regulation Machine Learning Single-Cell Analysis Gene Regulatory Networks Endothelial Cells Humans
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Machine learning using scRNA-seq Combined with bulk-seq to identify lactylation-related hub genes in carotid arteriosclerosis.

Scientific reports May 22, 2025
Atherosclerosis is a chronic inflammatory disease, this study aims to investigate the immune landscape in carotid atherosclerotic plaque formation and explore diagnostic biomarkers of lactylation-associated genes, so as to gain new insights into unde...
Carotid Artery Diseases Single-Cell Gene Expression Analysis Sequence Analysis, RNA Humans Plaque, Atherosclerotic Transcriptome Machine Learning Single-Cell Analysis RNA-Seq Biomarkers Gene Regulatory Networks Gene Expression Profiling
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Scmaskgan: masked multi-scale CNN and attention-enhanced GAN for scRNA-seq dropout imputation.

BMC bioinformatics May 20, 2025
Single-cell RNA sequencing (scRNA-seq) enables high-resolution analysis of cellular heterogeneity, but dropout events, where gene expression is undetected in individual cells, present a significant challenge. We propose scMASKGAN, which transforms ma...
Single-Cell Gene Expression Analysis Neural Networks, Computer Algorithms Sequence Analysis, RNA Neuroblastoma Humans Software Single-Cell Analysis RNA-Seq
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Machine learning and single-cell analysis uncover distinctive characteristics of CD300LG within the TNBC immune microenvironment: experimental validation.

Clinical and experimental medicine May 17, 2025
Investigating the essential function of CD300LG within the tumor microenvironment in triple-negative breast cancer (TNBC). Transcriptomic and single-cell data from TNBC were systematically collected and integrated. Four machine learning algorithms we...
Single-Cell Analysis Humans Female Receptors, Immunologic Gene Expression Regulation, Neoplastic Machine Learning Prognosis Tumor Microenvironment Triple Negative Breast Neoplasms Biomarkers, Tumor
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