AIMC Topic: Sequence Analysis, RNA

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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 Male Single-Cell Analysis Humans Testis Infertility, Male Spermatogenesis Single-Cell Gene Expression Analysis Sequence Analysis, RNA RNA-Seq
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Machine Learning Analysis Using RNA Sequencing to Distinguish Neuromyelitis Optica from Multiple Sclerosis and Identify Therapeutic Candidates.

The Journal of molecular diagnostics : JMD Mar 22, 2024
This study aims to identify RNA biomarkers distinguishing neuromyelitis optica (NMO) from relapsing-remitting multiple sclerosis (RRMS) and explore potential therapeutic applications leveraging machine learning (ML). An ensemble approach was develope...
Sequence Analysis, RNA Diagnosis, Differential Multiple Sclerosis Middle Aged Gene Expression Profiling Neuromyelitis Optica Multiple Sclerosis, Relapsing-Remitting Mitoxantrone Machine Learning Biomarkers Adult Male Female Humans
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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...
Neural Networks, Computer Computer Simulation Single-Cell Gene Expression Analysis Sequence Analysis, RNA Gene Expression Profiling Cluster Analysis Single-Cell Analysis
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BiPSTP: Sequence feature encoding method for identifying different RNA modifications with bidirectional position-specific trinucleotides propensities.

The Journal of biological chemistry Mar 5, 2024
RNA modification, a posttranscriptional regulatory mechanism, significantly influences RNA biogenesis and function. The accurate identification of modification sites is paramount for investigating their biological implications. Methods for encoding R...
RNA Processing, Post-Transcriptional Computational Biology Sequence Analysis, RNA Nucleotides RNA Support Vector Machine
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Distribution-Agnostic Deep Learning Enables Accurate Single-Cell Data Recovery and Transcriptional Regulation Interpretation.

Advanced science (Weinheim, Baden-Wurttemberg, Germany) Feb 21, 2024
Single-cell RNA sequencing (scRNA-seq) is a robust method for studying gene expression at the single-cell level, but accurately quantifying genetic material is often hindered by limited mRNA capture, resulting in many missing expression values. Exist...
Single-Cell Analysis Sequence Analysis, RNA Deep Learning Humans Gene Expression Profiling
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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...
Learning Biomedical Research Gene Expression Profiling Single-Cell Analysis Ecosystem Artificial Intelligence Algorithms Cluster Analysis Single-Cell Gene Expression Analysis Sequence Analysis, RNA
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PolyAMiner-Bulk is a deep learning-based algorithm that decodes alternative polyadenylation dynamics from bulk RNA-seq data.

Cell reports methods Feb 6, 2024
Alternative polyadenylation (APA) is a key post-transcriptional regulatory mechanism; yet, its regulation and impact on human diseases remain understudied. Existing bulk RNA sequencing (RNA-seq)-based APA methods predominantly rely on predefined anno...
RNA Polyadenylation RNA-Seq Sequence Analysis, RNA Algorithms Deep Learning Humans
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DeepVelo: deep learning extends RNA velocity to multi-lineage systems with cell-specific kinetics.

Genome biology Jan 19, 2024
Existing RNA velocity estimation methods strongly rely on predefined dynamics and cell-agnostic constant transcriptional kinetic rates, assumptions often violated in complex and heterogeneous single-cell RNA sequencing (scRNA-seq) data. Using a graph...
RNA Sequence Analysis, RNA Cell Differentiation Gene Expression Profiling Deep Learning Single-Cell Analysis
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Exploring the advances of single-cell RNA sequencing in thyroid cancer: a narrative review.

Medical oncology (Northwood, London, England) Dec 21, 2023
Thyroid cancer, a prevalent form of endocrine malignancy, has witnessed a substantial increase in occurrence in recent decades. To gain a comprehensive understanding of thyroid cancer at the single-cell level, this narrative review evaluates the appl...
Thyroid Neoplasms Sequence Analysis, RNA Cell Communication Machine Learning Humans Tumor Microenvironment Artificial Intelligence Gene Expression Profiling
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scNAT: a deep learning method for integrating paired single-cell RNA and T cell receptor sequencing profiles.

Genome biology Dec 18, 2023
Many deep learning-based methods have been proposed to handle complex single-cell data. Deep learning approaches may also prove useful to jointly analyze single-cell RNA sequencing (scRNA-seq) and single-cell T cell receptor sequencing (scTCR-seq) da...
Sequence Analysis, RNA Cell Movement Humans Cluster Analysis Gene Expression Profiling RNA Deep Learning Multiple Sclerosis Single-Cell Analysis
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