AIMC Topic: Single-Cell Analysis

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Deciphering lactate/lactylation networks in AML: integrated scRNA-seq and transcriptomics reveal functions and prognostic model.

BMC cancer
Acute myeloid leukemia (AML) exhibits pronounced heterogeneity, necessitating deep molecular characterization for precision therapy. Lactate metabolism and histone lactylation, influencing tumor biology via epigenetic regulation and immune microenvir...

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...

Identification of key diagnostic and prognostic biomarkers for aortic valve stenosis with coronary artery disease through immunological profiling integrating proteomics, single-cell sequencing, and machine learning.

Biochemical and biophysical research communications
BACKGROUND: Aortic valve stenosis with coronary artery disease (AS-CAD) represents a common yet complex cardiovascular comorbidity, characterized by multifactorial pathogenesis and a lack of specific serum biomarkers. These limitations hinder early d...

Identification of hub necroptosis-related targets and discovery of potential natural inhibitors in ulcerative colitis based on bioinformatics and computer-aided drug design.

Journal of computer-aided molecular design
Ulcerative colitis (UC) is a chronic inflammatory bowel disease with a complex pathogenesis and limited treatment options. Recently, necroptosis has been found to play a significant role in UC. This study aimed to investigate necroptosis-related mech...

Single-cell analysis of oxidative phosphorylation protein expression in pancreatic islets in type 2 diabetes.

The Journal of endocrinology
Mitochondrial dysfunction is a key feature of type 2 diabetes and is closely linked to ageing, a major risk factor for the disease. This study investigated islet cell composition and mitochondrial oxidative phosphorylation protein expression in pancr...

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 ...

Cell Decoder: decoding cell identity with multi-scale explainable deep learning.

Genome biology
BACKGROUND: Cells are the fundamental units of life, and understanding their diversity and functionality requires detailed characterization. The rise of single-cell omics data enables this, yet current deep learning approaches lack multi-scale interp...

Spatial domain identification method based on multi-view graph convolutional network and contrastive learning.

PLoS computational biology
Spatial transcriptomics is a rapidly developing field of single-cell genomics that quantitatively measures gene expression while providing spatial information within tissues. A key challenge in spatial transcriptomics is identifying spatially structu...

Single-cell multi-omics uncovers CPS1 as a breast cancer immune evasion therapeutic target.

Scientific reports
Despite significant advances in early detection and therapeutic interventions, breast cancer persists as the most frequently diagnosed malignancy and the leading cause of cancer-related deaths among women globally. Although multiple prognostic signat...

Backtracking metabolic dynamics in single cells predicts bacterial replication in human macrophages.

Nature communications
Accurately tracking dynamic state transitions is crucial for modeling and predicting biological outcomes, as it captures heterogeneity of cellular responses. To build a model to predict bacterial infection in single cells, we have monitored in parall...