AIMC Topic: Transcriptome

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Deep learning-based models for preimplantation mouse and human embryos based on single-cell RNA sequencing.

Nature methods Nov 14, 2024
The rapid growth of single-cell transcriptomic technology has produced an increasing number of datasets for both embryonic development and in vitro pluripotent stem cell-derived models. This avalanche of data surrounding pluripotency and the process ...
Blastocyst Embryonic Development Cell Lineage Pluripotent Stem Cells Humans Deep Learning Animals Single-Cell Analysis Gene Expression Profiling Mice Transcriptome Sequence Analysis, RNA
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Machine learning-driven discovery of novel therapeutic targets in diabetic foot ulcers.

Molecular medicine (Cambridge, Mass.) Nov 14, 2024
BACKGROUND: To utilize machine learning for identifying treatment response genes in diabetic foot ulcers (DFU).
Male Gene Expression Profiling Transcriptome Humans Single-Cell Analysis Machine Learning Computational Biology Biomarkers Wound Healing Female Diabetic Foot Calcium-Binding Proteins
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SpaInGNN: Enhanced clustering and integration of spatial transcriptomics based on refined graph neural networks.

Methods (San Diego, Calif.) Nov 13, 2024
Recent developments in spatial transcriptomics (ST) technology have markedly enhanced the proposed capacity to comprehensively characterize gene expression patterns within tissue microenvironments while crucially preserving spatial context. However, ...
Cluster Analysis Humans Gene Expression Profiling Neural Networks, Computer Transcriptome Algorithms Single-Cell Analysis Animals Mice
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Ferroptosis-related biomarkers for adamantinomatous craniopharyngioma treatment: conclusions from machine learning techniques.

Frontiers in endocrinology Nov 13, 2024
INTRODUCTION: Adamantinomatous craniopharyngioma (ACP) is difficult to cure completely and prone to recurrence after surgery. Ferroptosis as an iron-dependent programmed cell death, may be a critical process in ACP. The study aimed to screen diagnost...
Ferroptosis Pituitary Neoplasms Craniopharyngioma Male Humans Gene Expression Profiling Machine Learning Transcriptome Female Gene Expression Regulation, Neoplastic Biomarkers, Tumor
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Identification of TXN and F5 as novel diagnostic gene biomarkers of the severe asthma based on bioinformatics and machine learning analysis.

Autoimmunity Nov 12, 2024
Asthma poses a major threat to human health. The aim of this study was to identify genetic markers of severe asthma and analyze the relationship between key genes and immune infiltration. Differentially expressed genes (DEGs) were first screened by d...
Asthma Severity of Illness Index Gene Expression Profiling Transcriptome Computational Biology MicroRNAs Humans Gene Expression Regulation Machine Learning Thioredoxins Biomarkers
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Integration of Machine Learning and Experimental Validation to Identify Anoikis-Related Prognostic Signature for Predicting the Breast Cancer Tumor Microenvironment and Treatment Response.

Genes Nov 12, 2024
Anoikis-related genes (ANRGs) are crucial in the invasion and metastasis of breast cancer (BC). The underlying role of ANRGs in the prognosis of breast cancer patients warrants further study. The anoikis-related prognostic signature (ANRS) was gene...
Antineoplastic Agents Blotting, Western Imatinib Mesylate Gene Expression Profiling Machine Learning Transcriptome Proportional Hazards Models Prognosis Databases, Genetic Breast Neoplasms Real-Time Polymerase Chain Reaction Anoikis Female Predictive Value of Tests Tumor Microenvironment Reverse Transcriptase Polymerase Chain Reaction Reproducibility of Results Drug Screening Assays, Antitumor Biomarkers, Tumor Immunotherapy Aged Gene Expression Enzyme-Linked Immunosorbent Assay Middle Aged Treatment Outcome
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Discovery of key molecular signatures for diagnosis and therapies of glioblastoma by combining supervised and unsupervised learning approaches.

Scientific reports Nov 11, 2024
Glioblastoma (GBM) is the most malignant brain cancer and one of the leading causes of cancer-related death globally. So, identifying potential molecular signatures and associated drug molecules are crucial for diagnosis and therapies of GBM. This st...
Gene Expression Profiling Transcriptome Gene Regulatory Networks Gene Expression Regulation, Neoplastic Humans Biomarkers, Tumor Brain Neoplasms Molecular Docking Simulation DNA Methylation Unsupervised Machine Learning Glioblastoma Supervised Machine Learning
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DeSide: A unified deep learning approach for cellular deconvolution of tumor microenvironment.

Proceedings of the National Academy of Sciences of the United States of America Nov 8, 2024
Cellular deconvolution via bulk RNA sequencing (RNA-seq) presents a cost-effective and efficient alternative to experimental methods such as flow cytometry and single-cell RNA-seq (scRNA-seq) for analyzing the complex cellular composition of tumor mi...
Humans Tumor Microenvironment Neoplasms Gene Expression Profiling RNA-Seq Transcriptome Sequence Analysis, RNA Deep Learning Gene Expression Regulation, Neoplastic Cell Line, Tumor Single-Cell Analysis
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Interpretable machine learning uncovers epithelial transcriptional rewiring and a role for Gelsolin in COPD.

JCI insight Nov 8, 2024
Transcriptomic analyses have advanced the understanding of complex disease pathophysiology including chronic obstructive pulmonary disease (COPD). However, identifying relevant biologic causative factors has been limited by the integration of high di...
Machine Learning Female Pulmonary Disease, Chronic Obstructive Animals Humans Gene Regulatory Networks Mice Male Disease Models, Animal Lung Epithelial Cells Gene Expression Profiling Gelsolin Transcriptome
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Comprehensive Analysis of Immune Infiltration and Key Genes in Peri-Implantitis Using Bioinformatics and Molecular Biology Approaches.

Medical science monitor : international medical journal of experimental and clinical research Nov 6, 2024
BACKGROUND Peri-implantitis is the main cause of failure of implant treatment, and there is little research on its molecular mechanism. This study aimed to identify key biomarkers and immune infiltration of peri-implantitis using a bioinformatics met...
Gene Ontology Molecular Biology Peri-Implantitis Algorithms Biomarkers Gene Expression Profiling Transcriptome Gene Regulatory Networks Humans Computational Biology Support Vector Machine Databases, Genetic
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