AIMC Topic: Transcriptome

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Leveraging autoencoder models and data augmentation to uncover transcriptomic diversity of gingival keratinocytes in single cell analysis.

Scientific reports
Periodontitis, a chronic inflammatory condition of the periodontium, is associated with over 60 systemic diseases. Despite advancements, precision medicine approaches have had limited success, emphasizing the need for deeper insights into cellular su...

Identification of potential pathogenic genes associated with the comorbidity of rheumatoid arthritis and renal fibrosis using bioinformatics and machine learning.

Scientific reports
This study aimed to identify the potential pathogenic genes associated with the comorbidity of rheumatoid arthritis (RA) and renal fibrosis (RF). Transcriptomic data related to RA and RF were retrieved from the GEO database. Differential expression g...

Potential role of TNFRSF12A in linking glioblastoma and alzheimer's disease via shared tumour suppressor pathways.

Scientific reports
Tumor suppressor genes (TSGs) are critical regulators of cellular homeostasis and are extensively studied in cancer biology. However, their roles in neurodegenerative diseases, particularly Alzheimer's disease (AD), remain poorly understood. Recent e...

Shared gene signatures and molecular mechanisms link ankylosing spondylitis and rheumatoid arthritis.

Scientific reports
Ankylosing spondylitis (AS) and rheumatoid arthritis (RA) are closely related autoimmune diseases with shared mechanisms that remain unclear. This study aims to identify shared molecular signatures and hub genes underlying the co-occurrence of AS and...

Integrated analysis of shared gene expression signatures and immune microenvironment heterogeneity in type 2 diabetes mellitus and colorectal cancer.

Scientific reports
Emerging evidence suggests a bidirectional relationship between colorectal cancer (CRC) and type 2 diabetes mellitus (T2DM), yet the shared molecular mechanisms and prognostic biomarkers remain poorly characterized. This study aimed to identify novel...

Dissecting crosstalk induced by cell-cell communication using single-cell transcriptomic data.

Nature communications
During cell-cell communication (CCC), pathways activated by different ligand-receptor pairs may have crosstalk with each other. While multiple methods have been developed to infer CCC networks and their downstream response using single-cell RNA-seq d...

Screening biomarkers related to cholesterol metabolism in osteoarthritis based on transcriptomics.

Scientific reports
Cholesterol metabolism-related genes (CMRGs) have been associated with osteoarthritis (OA), but their specific regulatory mechanisms remain unclear. This study aimed to investigate the role of CMRGs in OA and provide new insights into its treatment. ...

Identification of pyroptosis related genes and subtypes in atherosclerosis using multiomic and single cell analysis.

Scientific reports
Atherosclerosis (AS), the leading cause of cardiovascular diseases, is a chronic inflammatory disorder involving lipid metabolism, immune dysregulation, and cell death. Pyroptosis, a form of inflammatory programmed cell death, is implicated in AS pro...

CellMemory: hierarchical interpretation of out-of-distribution cells using bottlenecked transformer.

Genome biology
Machine learning methods, especially Transformer architectures, have been widely employed in single-cell omics studies. However, interpretability and accurate representation of out-of-distribution (OOD) cells remains challenging. Inspired by the glob...

Transcriptomic analysis reveals novel targets in benign schwannoma using machine learning.

Neuroscience
BACKGROUND & OBJECTIVE: This study aimed to identify key immune-related biomarkers of benign schwannoma through machine learning-assisted transcriptomic and single-cell analyses, and to construct a predictive model for disease evaluation.