AIMC Topic: Single-Cell Gene Expression Analysis

Clear Filters Showing 21 to 30 of 70 articles

Investigation of cell development and tissue structure network based on natural Language processing of scRNA-seq data.

Journal of translational medicine
BACKGROUND: Single-cell multi-omics technologies, particularly single-cell RNA sequencing (scRNA-seq), have revolutionized our understanding of cellular heterogeneity and development by providing insights into gene expression at the single-cell level...

The Role of Autophagy and Cell Communication in COPD Progression: Insights from Bioinformatics and scRNA-seq.

COPD
Chronic obstructive pulmonary disease (COPD) is characterized by restricted airflow that leads to significant respiratory difficulties. This progressive disease often results in diminished pulmonary function and the onset of additional respiratory co...

Deciphering the role of metal ion transport-related genes in T2D pathogenesis and immune cell infiltration via scRNA-seq and machine learning.

Frontiers in immunology
INTRODUCTION: Type 2 diabetes (T2D) is a complex metabolic disorder with significant global health implications. Understanding the molecular mechanisms underlying T2D is crucial for developing effective therapeutic strategies. This study employs sing...

Integrating single-cell RNA-Seq and machine learning to dissect tryptophan metabolism in ulcerative colitis.

Journal of translational medicine
BACKGROUND: Ulcerative colitis (UC) is a persistent inflammatory bowels disease (IBD) characterized by immune response dysregulation and metabolic disruptions. Tryptophan metabolism has been believed as a significant factor in UC pathogenesis, with s...

Integration of bulk/scRNA-seq and multiple machine learning algorithms identifies PIM1 as a biomarker associated with cuproptosis and ferroptosis in abdominal aortic aneurysm.

Frontiers in immunology
BACKGROUND: Abdominal aortic aneurysm (AAA) is a serious life-threatening vascular disease, and its ferroptosis/cuproptosis markers have not yet been characterized. This study was aiming to identify markers associated with ferroptosis/cuproptosis in ...

Essential blood molecular signature for progression of sepsis-induced acute lung injury: Integrated bioinformatic, single-cell RNA Seq and machine learning analysis.

International journal of biological macromolecules
In this study, we aimed to identify an essential blood molecular signature for chacterizing the progression of sepsis-induced acute lung injury using integrated bioinformatic and machine learning analysis. The results showed that a total of 88 functi...

Integrating large-scale single-cell RNA sequencing in central nervous system disease using self-supervised contrastive learning.

Communications biology
The central nervous system (CNS) comprises a diverse range of brain cell types with distinct functions and gene expression profiles. Although single-cell RNA sequencing (scRNA-seq) provides new insights into the brain cell atlases, integrating large-...

Machine-learning and scRNA-Seq-based diagnostic and prognostic models illustrating survival and therapy response of lung adenocarcinoma.

Genes and immunity
Lung cancer is a major cause accounting for cancer-related mortalities, with lung adenocarcinoma (LUAD) being the most prevalent subtype. Given the high clinical and cellular heterogeneities of LUAD, accurate diagnosis and prognosis are crucial to av...