AIMC Topic: Sequence Analysis, RNA

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scSemiPLC: a semi-supervised learning framework for annotating single-cell RNA-Seq data by generating pseudo-labels through clustering.

mSystems
UNLABELLED: Single-cell RNA sequencing (scRNA-seq) technology enables researchers to explore heterogeneity of diverse cell types within complex tissues at the single-cell resolution. Cell annotation, as a crucial step in scRNA-seq data analysis, prov...

Identification and validation of PANoptosis-related biomarkers in Alzheimer's disease via single-cell RNA sequencing and machine learning.

European journal of medical research
BACKGROUND: Alzheimer's disease (AD) is a progressive neurodegenerative disorder with complex underlying mechanisms. PANoptosis, a newly defined form of programmed cell death that integrates pyroptosis, apoptosis, and necroptosis, may play a crucial ...

Benchmarking deep learning methods for biologically conserved single-cell integration.

Genome biology
BACKGROUND: Advancements in single-cell RNA sequencing have enabled the analysis of millions of cells, but integrating such data across samples and methods while mitigating batch effects remains challenging. Deep learning approaches address this by l...

Denoising single-cell RNA-seq data with a deep learning-embedded statistical framework.

BMC bioinformatics
BACKGROUND: Single-cell RNA sequencing (scRNA-seq) provides extensive opportunities to explore cellular heterogeneity but is often limited by substantial technical noise and variability. The prevalence of zero counts, arising from both biological var...

scMFF: a machine learning framework with multiple feature fusion strategies for cell type identification.

BMC bioinformatics
Accurate cell type classification is critical for downstream analysis in single-cell RNA sequencing (scRNA-seq). Most existing methods rely on a single type of feature representation-such as statistical, information theory, matrix factorization, or d...

Integrating bulk and single-cell RNA sequencing data to dissect genetic links between periodontitis and obstructive sleep apnea.

Sleep & breathing = Schlaf & Atmung
PURPOSE: Periodontitis (PD) and obstructive sleep apnea (OSA) are widespread conditions with profound health consequences. Increasing evidence suggests shared pathophysiological mechanisms between PD and OSA, prompting this study to explore their gen...

Deep structural clustering reveals hidden systematic biases in RNA sequencing data.

Genome research
RNA sequencing (RNA-seq) is a pivotal tool for transcriptomic analysis, providing comprehensive exploration of gene expression across diverse biological contexts. However, RNA-seq data are susceptible to various biases that can significantly compromi...

Gene expression signatures from whole blood predict amyotrophic lateral sclerosis case status and survival.

Nature communications
Amyotrophic lateral sclerosis (ALS) is a rare and fatal neurodegenerative disease with a median survival of only 2 to 4 years from diagnosis. Improved tools are needed to shorten diagnostic delays and improve prognostication to benefit clinical care....

Research progress of single cell RNA sequencing in nervous system.

Molecular biology reports
Single-cell RNA sequencing (scRNA-seq) and its integration with multi-omics technologies such as epigenomics and spatial transcriptomics are revolutionizing our traditional understanding of cellular heterogeneity and the microenvironment in the nervo...