AIMC Topic: RNA-Seq

Clear Filters Showing 141 to 150 of 181 articles

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...
Sequence Analysis, RNA Neuroblastoma Humans Neural Networks, Computer Software RNA-Seq Single-Cell Gene Expression Analysis Algorithms Single-Cell Analysis
View on PubMed DOI

scMUSCL: multi-source transfer learning for clustering scRNA-seq data.

Bioinformatics (Oxford, England) May 6, 2025
MOTIVATION: Single-cell RNA sequencing (scRNA-seq) analysis relies heavily on effective clustering to facilitate numerous downstream applications. Although several machine learning methods have been developed to enhance single-cell clustering, most a...
Humans Neural Networks, Computer Machine Learning Software Single-Cell Gene Expression Analysis Sequence Analysis, RNA Algorithms Cluster Analysis Single-Cell Analysis RNA-Seq
View on PubMed DOI

Decoupled GNNs based on multi-view contrastive learning for scRNA-seq data clustering.

Briefings in bioinformatics May 1, 2025
Clustering is pivotal in deciphering cellular heterogeneity in single-cell RNA sequencing (scRNA-seq) data. However, it suffers from several challenges in handling the high dimensionality and complexity of scRNA-seq data. Especially when employing gr...
Neural Networks, Computer Machine Learning Algorithms Humans Single-Cell Gene Expression Analysis Animals Computational Biology Sequence Analysis, RNA Single-Cell Analysis Cluster Analysis RNA-Seq
View on PubMed DOI

Oxidative Phosphorylation Pathway in Ankylosing Spondylitis: Multi-Omics Analysis and Machine Learning.

International journal of rheumatic diseases May 1, 2025
INTRODUCTION: Ankylosing spondylitis (AS) is a chronic inflammatory disease affecting the axial skeleton, characterized by immune microenvironment dysregulation and elevated cytokines like TNF-α and IL-17. Mitochondrial oxidative phosphorylation (OXP...
Gene Regulatory Networks Multiomics Signal Transduction Case-Control Studies Single-Cell Analysis RNA-Seq Mitochondria Oxidative Phosphorylation Spondylitis, Ankylosing Adult Male Middle Aged Leukocytes, Mononuclear Gene Expression Profiling Transcriptome Humans Machine Learning Female
View on PubMed DOI

CoupleVAE: coupled variational autoencoders for predicting perturbational single-cell RNA sequencing data.

Briefings in bioinformatics Mar 4, 2025
With the rapid advances in single-cell sequencing technology, it is now feasible to conduct in-depth genetic analysis in individual cells. Study on the dynamics of single cells in response to perturbations is of great significance for understanding t...
Algorithms Deep Learning Humans Sequence Analysis, RNA Single-Cell Analysis Autoencoder RNA-Seq Computational Biology
View on PubMed DOI

COME: contrastive mapping learning for spatial reconstruction of single-cell RNA sequencing data.

Bioinformatics (Oxford, England) Mar 4, 2025
MOTIVATION: Single-cell RNA sequencing (scRNA-seq) enables high-throughput transcriptomic profiling at single-cell resolution. The inherent spatial location is crucial for understanding how single cells orchestrate multicellular functions and drive d...
Computational Biology Sequence Analysis, RNA High-Throughput Nucleotide Sequencing Machine Learning Software Algorithms Single-Cell Analysis RNA-Seq Gene Expression Profiling Transcriptome Humans
View on PubMed DOI

stAI: a deep learning-based model for missing gene imputation and cell-type annotation of spatial transcriptomics.

Nucleic acids research Feb 27, 2025
Spatial transcriptomics technology has revolutionized our understanding of cellular systems by capturing RNA transcript levels in their original spatial context. Single-cell spatial transcriptomics (scST) offers single-cell resolution expression leve...
Single-Cell Analysis RNA-Seq Sequence Analysis, RNA Molecular Sequence Annotation Gene Expression Profiling Transcriptome Deep Learning Humans Software Animals
View on PubMed DOI

Machine learning-optimized targeted detection of alternative splicing.

Nucleic acids research Jan 24, 2025
RNA sequencing (RNA-seq) is widely adopted for transcriptome analysis but has inherent biases that hinder the comprehensive detection and quantification of alternative splicing. To address this, we present an efficient targeted RNA-seq method that gr...
RNA-Seq Humans High-Throughput Nucleotide Sequencing Machine Learning Sequence Analysis, RNA Algorithms Alternative Splicing
View on PubMed DOI

CSI-GEP: A GPU-based unsupervised machine learning approach for recovering gene expression programs in atlas-scale single-cell RNA-seq data.

Cell genomics Jan 8, 2025
Exploratory analysis of single-cell RNA sequencing (scRNA-seq) typically relies on hard clustering over two-dimensional projections like uniform manifold approximation and projection (UMAP). However, such methods can severely distort the data and hav...
Mice Humans Sequence Analysis, RNA Single-Cell Analysis Brain Unsupervised Machine Learning RNA-Seq Animals Single-Cell Gene Expression Analysis Gene Expression Profiling
View on PubMed DOI

Applying AI/ML for Analyzing Gene Expression Patterns.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2025
Artificial intelligence (AI) and machine learning (ML) have advanced in several areas and fields of life; however, its progress in the field of genomics is not matching the levels others have achieved. Challenges include but are not limited to the ha...
Genomics Gene Expression Profiling Humans Computational Biology Transcriptome Artificial Intelligence RNA-Seq Machine Learning
View on PubMed DOI
Popular Topics
Recent Journals