AIMC Topic: Sequence Analysis, RNA

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Machine learning algorithms integrate bulk and single-cell RNA data to reveal the crosstalk and heterogeneity of NOTCH and autophagy activity following idiopathic pulmonary fibrosis.

International immunopharmacology Jun 9, 2025
BACKGROUND: NOTCH and autophagy significantly impact the pathogenesis of idiopathic pulmonary fibrosis (IPF); however, studies exploring their heterogeneity and potential correlation at the single-cell level are still lacking. Identifying the feature...
Single-Cell Analysis Sequence Analysis, RNA Signal Transduction Humans Machine Learning Algorithms Idiopathic Pulmonary Fibrosis Receptors, Notch Fibroblasts Autophagy
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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...
Sequence Analysis, RNA Cluster Analysis Principal Component Analysis Single-Cell Analysis RNA-Seq Single-Cell Gene Expression Analysis Humans Machine Learning
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SC2Spa: a deep learning based approach to map transcriptome to spatial origins at cellular resolution.

BMC bioinformatics Jun 2, 2025
BACKGROUND: Understanding cellular heterogeneity within tissues hinges on knowledge of their spatial context. However, it is still challenging to accurately map cells to their spatial coordinates.
Humans Animals Gene Expression Profiling Transcriptome Deep Learning Single-Cell Analysis RNA-Seq Sequence Analysis, RNA
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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...
Algorithms Single-Cell Analysis RNA-Seq Single-Cell Gene Expression Analysis Sequence Analysis, RNA Autoencoder Humans Neural Networks, Computer Software
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GRACE: Unveiling Gene Regulatory Networks With Causal Mechanistic Graph Neural Networks in Single-Cell RNA-Sequencing Data.

IEEE transactions on neural networks and learning systems May 2, 2025
Reconstructing gene regulatory networks (GRNs) using single-cell RNA sequencing (scRNA-seq) data holds great promise for unraveling cellular fate development and heterogeneity. While numerous machine-learning methods have been proposed to infer GRNs ...
Graph Neural Networks Single-Cell Analysis Gene Regulatory Networks Machine Learning Sequence Analysis, RNA Humans Algorithms Neural Networks, Computer
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Integrative Analysis of Lactylation-Associated Features in Abdominal Aortic Aneurysm and Its Immune Microenvironment Utilizing scRNA-seq and Bulk RNA Sequencing.

Circulation journal : official journal of the Japanese Circulation Society Apr 29, 2025
BACKGROUND: Abdominal aortic aneurysm (AAA) is a vascular disease strongly associated with immune dysregulation and metabolic disturbances. Although lactate metabolism and its associated process, lactylation, have been implicated in various diseases,...
Aged Animals Male Humans Mice Female Single-Cell Analysis Sequence Analysis, RNA RNA-Seq Aortic Aneurysm, Abdominal Single-Cell Gene Expression Analysis
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ScAGCN: Graph Convolutional Network with Adaptive Aggregation Mechanism for scRNA-seq Data Dimensionality Reduction.

Interdisciplinary sciences, computational life sciences Apr 25, 2025
With the development of single-cell RNA-sequencing (scRNA-seq) technology, scRNA-seq data analysis suffers huge challenges due to large scale, high dimensionality, high noise, and high sparsity. To achieve accurately embedded representation in the la...
Dimensionality Reduction Single-Cell Gene Expression Analysis Algorithms Computational Biology Humans Sequence Analysis, RNA Single-Cell Analysis RNA-Seq Neural Networks, Computer
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TransAnno-Net: A Deep Learning Framework for Accurate Cell Type Annotation of Mouse Lung Tissue Using Self-supervised Pretraining.

Computer methods and programs in biomedicine Apr 24, 2025
BACKGROUND: Single-cell RNA sequencing (scRNA-seq) has become a significant tool for addressing complex issuess in the field of biology. In the context of scRNA-seq analysis, it is imperative to accurately determine the type of each cell. However, co...
Computational Biology Sequence Analysis, RNA Supervised Machine Learning Deep Learning Single-Cell Analysis Mice Algorithms Animals Lung
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Transfer learning of multicellular organization via single-cell and spatial transcriptomics.

PLoS computational biology Apr 21, 2025
Biological tissues exhibit complex gene expression and multicellular patterns that are valuable to dissect. Single-cell RNA sequencing (scRNA-seq) provides full coverages of genes, but lacks spatial information, whereas spatial transcriptomics (ST) m...
Humans Machine Learning Transcriptome Computational Biology Neural Networks, Computer Single-Cell Analysis Animals Sequence Analysis, RNA Gene Expression Profiling Drosophila Mice
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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...
Deep Learning Sequence Analysis, RNA Single-Cell Analysis Gene Regulatory Networks Humans RNA-Seq Single-Cell Gene Expression Analysis Machine Learning Computational Biology Algorithms
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