AIMC Topic: Single-Cell Analysis

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Screening and validating genes associated with cuproptosis in systemic lupus erythematosus by expression profiling combined with machine learning.

Biomolecules & biomedicine Mar 7, 2025
Cell death has long been a focal point in life sciences research, and recently, scientists have discovered a novel form of cell death induced by copper, termed cuproptosis. This paper aimed to identify genes associated with cuproptosis in systemic lu...
Machine Learning Female Gene Expression Profiling Humans Databases, Genetic Lupus Erythematosus, Systemic Copper Transcriptome ROC Curve Single-Cell Analysis
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scHeteroNet: A Heterophily-Aware Graph Neural Network for Accurate Cell Type Annotation and Novel Cell Detection.

Advanced science (Weinheim, Baden-Wurttemberg, Germany) Mar 5, 2025
Single-cell RNA sequencing (scRNA-seq) has unveiled extensive cellular heterogeneity, yet precise cell type annotation and the identification of novel cell populations remain significant challenges. scHeteroNet, a novel graph neural network framework...
Graph Neural Networks Neural Networks, Computer Single-Cell Analysis Sequence Analysis, RNA Humans
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Investigation of cell development and tissue structure network based on natural Language processing of scRNA-seq data.

Journal of translational medicine Mar 4, 2025
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...
Humans Animals Single-Cell Gene Expression Analysis Sequence Analysis, RNA Natural Language Processing Single-Cell Analysis RNA-Seq Gene Regulatory Networks Cell Differentiation Organ Specificity
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The role of senescence-related genes in major depressive disorder: insights from machine learning and single cell analysis.

BMC psychiatry Mar 3, 2025
BACKGROUND: Evidence indicates that patients with Major Depressive Disorder (MDD) exhibit a senescence phenotype or an increased susceptibility to premature senescence. However, the relationship between senescence-related genes (SRGs) and MDD remains...
Gene Regulatory Networks Cellular Senescence Male Aging Middle Aged Depressive Disorder, Major Case-Control Studies Machine Learning Single-Cell Analysis Female Adult Humans
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Multi-omics analyses and machine learning prediction of oviductal responses in the presence of gametes and embryos.

eLife Feb 26, 2025
The oviduct is the site of fertilization and preimplantation embryo development in mammals. Evidence suggests that gametes alter oviductal gene expression. To delineate the adaptive interactions between the oviduct and gamete/embryo, we performed a m...
Fallopian Tubes Germ Cells Oviducts Transcriptome Spermatozoa Machine Learning Single-Cell Analysis Embryo, Mammalian Mice Multiomics Embryonic Development Female Proteomics Animals Mice, Inbred C57BL Male
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Development of a tertiary lymphoid structure-based prognostic model for breast cancer: integrating single-cell sequencing and machine learning to enhance patient outcomes.

Frontiers in immunology Feb 26, 2025
BACKGROUND: Breast cancer, a highly prevalent global cancer, poses significant challenges, especially in advanced stages. Prognostic models are crucial to enhance patient outcomes. Tertiary lymphoid structures (TLS) within the tumor microenvironment ...
Tumor Microenvironment Prognosis Lymphocytes, Tumor-Infiltrating Biomarkers, Tumor Female Humans Tertiary Lymphoid Structures Single-Cell Analysis Breast Neoplasms Machine Learning
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Multiscale Dissection of Spatial Heterogeneity by Integrating Multi-Slice Spatial and Single-Cell Transcriptomics.

Advanced science (Weinheim, Baden-Wurttemberg, Germany) Feb 25, 2025
The spatial structure of cells is highly organized at multiscale levels from global spatial domains to local cell type heterogeneity. Existing methods for analyzing spatially resolved transcriptomics (SRT) are separately designed for either domain al...
Single-Cell Analysis Humans Gene Expression Profiling Transcriptome Deep Learning
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Evaluating feature extraction in ovarian cancer cell line co-cultures using deep neural networks.

Communications biology Feb 25, 2025
Single-cell image analysis is crucial for studying drug effects on cellular morphology and phenotypic changes. Most studies focus on single cell types, overlooking the complexity of cellular interactions. Here, we establish an analysis pipeline to ex...
Female Antineoplastic Agents Cell Line, Tumor Single-Cell Analysis Fibroblasts Ovarian Neoplasms Humans Neural Networks, Computer Phenotype Coculture Techniques
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A novel coarsened graph learning method for scalable single-cell data analysis.

Computers in biology and medicine Feb 24, 2025
The emergence of single-cell technologies, including flow and mass cytometry, as well as single-cell RNA sequencing, has revolutionized the study of cellular heterogeneity, generating vast datasets rich in biological insights. Despite the effectivene...
Computational Biology Sequence Analysis, RNA Machine Learning Algorithms Single-Cell Analysis Humans Neural Networks, Computer
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Deep learning imputes DNA methylation states in single cells and enhances the detection of epigenetic alterations in schizophrenia.

Cell genomics Feb 21, 2025
DNA methylation (DNAm) is a key epigenetic mark with essential roles in gene regulation, mammalian development, and human diseases. Single-cell technologies enable profiling DNAm at cytosines in individual cells, but they often suffer from low covera...
Mice Epigenesis, Genetic DNA Methylation Schizophrenia CpG Islands Animals Deep Learning Single-Cell Analysis Humans
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