AIMC Topic: Single-Cell Gene Expression Analysis

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Identification of Marker Genes in Infectious Diseases from ScRNA-seq Data Using Interpretable Machine Learning.

International journal of molecular sciences May 29, 2024
A common result of infection is an abnormal immune response, which may be detrimental to the host. To control the infection, the immune system might undergo regulation, therefore producing an excess of either pro-inflammatory or anti-inflammatory pat...
COVID-19 Biomarkers SARS-CoV-2 Humans Machine Learning Single-Cell Gene Expression Analysis Sequence Analysis, RNA Sepsis Gene Expression Profiling Single-Cell Analysis Transcriptome RNA-Seq
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A deep learning framework for denoising and ordering scRNA-seq data using adversarial autoencoder with dynamic batching.

STAR protocols May 14, 2024
Single-cell RNA sequencing (scRNA-seq) provides high resolution of cell-to-cell variation in gene expression and offers insights into cell heterogeneity, differentiating dynamics, and disease mechanisms. However, technical challenges such as low capt...
Humans Single-Cell Gene Expression Analysis Sequence Analysis, RNA Deep Learning Single-Cell Analysis RNA-Seq
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Unveiling the molecular complexity of proliferative diabetic retinopathy through scRNA-seq, AlphaFold 2, and machine learning.

Frontiers in endocrinology May 10, 2024
BACKGROUND: Proliferative diabetic retinopathy (PDR), a major cause of blindness, is characterized by complex pathogenesis. This study integrates single-cell RNA sequencing (scRNA-seq), Non-negative Matrix Factorization (NMF), machine learning, and A...
Humans Sequence Analysis, RNA Male Protein Interaction Maps Molecular Docking Simulation RNA-Seq Case-Control Studies Diabetic Retinopathy Oxidative Stress Single-Cell Gene Expression Analysis Machine Learning Single-Cell Analysis Female
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Identifying gene expression programs in single-cell RNA-seq data using linear correlation explanation.

Journal of biomedical informatics Apr 15, 2024
OBJECTIVE: Gene expression analysis through single-cell RNA sequencing (scRNA-seq) has revolutionized our understanding of gene regulation in diverse cell types, tissues, and organisms. While existing methods primarily focus on identifying cell type-...
Single-Cell Gene Expression Analysis Mice Computational Biology Colon Gene Expression Profiling RNA-Seq Dentate Gyrus Humans Machine Learning Algorithms Animals
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The human infertility single-cell testis atlas (HISTA): an interactive molecular scRNA-Seq reference of the human testis.

Andrology Apr 5, 2024
BACKGROUND: Single-cell RNA-seq (scRNA-Seq) has been widely adopted to study gene expression of the human testis. Several datasets of scRNA-Seq from human testis have been generated from different groups processed with different informatics pipelines...
Adult Testis Male RNA-Seq Infertility, Male Single-Cell Analysis Humans Spermatogenesis Single-Cell Gene Expression Analysis Sequence Analysis, RNA
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scFSNN: a feature selection method based on neural network for single-cell RNA-seq data.

BMC genomics Mar 8, 2024
While single-cell RNA sequencing (scRNA-seq) allows researchers to analyze gene expression in individual cells, its unique characteristics like over-dispersion, zero-inflation, high gene-gene correlation, and large data volume with many features pose...
Sequence Analysis, RNA Cluster Analysis Gene Expression Profiling Single-Cell Analysis Single-Cell Gene Expression Analysis Neural Networks, Computer Computer Simulation
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scMGCN: A Multi-View Graph Convolutional Network for Cell Type Identification in scRNA-seq Data.

International journal of molecular sciences Feb 13, 2024
Single-cell RNA sequencing (scRNA-seq) data reveal the complexity and diversity of cellular ecosystems and molecular interactions in various biomedical research. Hence, identifying cell types from large-scale scRNA-seq data using existing annotations...
Artificial Intelligence Algorithms Learning Biomedical Research Ecosystem Gene Expression Profiling Sequence Analysis, RNA Single-Cell Analysis Cluster Analysis Single-Cell Gene Expression Analysis
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A New Graph Autoencoder-Based Consensus-Guided Model for scRNA-seq Cell Type Detection.

IEEE transactions on neural networks and learning systems Feb 5, 2024
Single-cell RNA sequencing (scRNA-seq) technology is famous for providing a microscopic view to help capture cellular heterogeneity. This characteristic has advanced the field of genomics by enabling the delicate differentiation of cell types. Howeve...
Algorithms Learning Single-Cell Gene Expression Analysis Consensus Neural Networks, Computer Genomics Cluster Analysis
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Integrated analysis of single-cell RNA-seq and chipset data unravels PANoptosis-related genes in sepsis.

Frontiers in immunology Jan 3, 2024
BACKGROUND: The poor prognosis of sepsis warrants the investigation of biomarkers for predicting the outcome. Several studies have indicated that PANoptosis exerts a critical role in tumor initiation and development. Nevertheless, the role of PANopto...
Cell Transformation, Neoplastic Sepsis Humans Single-Cell Gene Expression Analysis Algorithms B-Lymphocytes
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On the use of QDE-SVM for gene feature selection and cell type classification from scRNA-seq data.

PloS one Oct 19, 2023
Cell type identification is one of the fundamental tasks in single-cell RNA sequencing (scRNA-seq) studies. It is a key step to facilitate downstream interpretations such as differential expression, trajectory inference, etc. scRNA-seq data contains ...
Support Vector Machine Cluster Analysis Single-Cell Gene Expression Analysis Sequence Analysis, RNA Machine Learning Algorithms Gene Expression Profiling Transcriptome Single-Cell Analysis
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