AIMC Topic: Sequence Analysis, RNA

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GraphComm predicts cell cell communication using a graph based deep learning method in single cell RNA sequencing data.

Scientific reports
Interactions between cells coordinate various functions across cell-types in health and disease states. Novel single-cell techniques enable deep investigation of cellular crosstalk at single-cell resolution. Cell-cell communication (CCC) is mediated ...

Single-cell RNA-seq combined with bulk RNA-seq analysis identifies necroptosis-related genes as therapeutic targets for periodontitis.

BMC medical genomics
BACKGROUND: Necroptosis, a regulated form of programmed cell death, exacerbates inflammatory responses by releasing damage-associated molecular patterns and inflammatory factors. However, the specific mechanisms underlying necroptosis in periodontiti...

Identification of lipid metabolism-related signature in nonalcoholic fatty liver: evidences from transcriptomics and single cell RNA-sequencing analysis.

European journal of medical research
BACKGROUND: Considering the complex and close-knit relationship between non-alcoholic fatty liver disease (NAFLD) and the metabolic status, this study aimed to identify lipid metabolism-related genes (LMGs), construct an effective diagnostic model, a...

Single-cell RNA sequencing and Mendelian randomization, revealing molecular mechanisms and causal correlation of immune-related genes in periodontitis.

Scientific reports
The immune system has been linked to periodontitis risk in oral inflammation and systemic consequences. Specifically, this study investigated whether hub genes were associated with immune cells via integrating single-cell RNA sequencing (scRNA-seq) a...

DeepRNA-Reg: a deep-learning based approach for comparative analysis of CLIP experiments.

RNA biology
DeepRNA-Reg employs advances in deep learning to enable high-fidelity comparative analysis of paired datasets of high-throughput sequencing of RNA isolated by crosslinking immunoprecipitation (HITS-CLIP). In a HITS-CLIP experimental paradigm where Ag...

Paired snRNA-seq and scRNA-seq analysis of MASLD patients to identify early-stage markers for disease progression.

Hepatology communications
BACKGROUND AND AIMS: Metabolic dysfunction-associated steatotic liver disease (MASLD) is a leading cause of chronic liver disease worldwide. Progression from simple metabolic dysfunction-associated steatotic liver (MASL) without necro-inflammation to...

Single-cell RNA-sequencing of circulating tumour cells: A practical guide to workflow and translational applications.

Cancer metastasis reviews
The global burden of cancer is rising, with treatment failures often due to the metastatic nature of late-stage malignancies. Circulating tumour cells (CTCs) are metastatic precursors shed from primary tumours, which survive in circulation, extravasa...

scKAN: interpretable single-cell analysis for cell-type-specific gene discovery and drug repurposing via Kolmogorov-Arnold networks.

Genome biology
BACKGROUND: Analysis of single-cell RNA sequencing (scRNA-seq) data has revolutionized our understanding of cellular heterogeneity, yet current approaches face challenges in efficiency, interpretability, and connecting molecular insights to therapeut...

Comprehensive characterization of the molecular feature of acetylation in colorectal cancer using integrated single-cell and bulk RNA sequencing.

Scientific reports
Colorectal cancer (CRC) remains a major global health burden with high mortality rates, underscoring the need for effective therapies. This study explores the acetylation characteristics in CRC using single-cell RNA sequencing (scRNA-seq) and weighte...

E2-regulated transcriptome complexity revealed by long-read direct RNA sequencing: from isoform discovery to truncated proteins.

RNA biology
Oestrogen receptor alpha (ERα)-positive (ER+) breast cancers are driven by the binding of 17β-oestradiol (E2) to ERα, which transcriptionally regulates target genes. Although microarrays and conventional RNA sequencing have identified E2 target genes...