AIMC Topic: Gene Expression Profiling

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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).
Biomarkers Female Male Gene Expression Profiling Transcriptome Single-Cell Analysis Computational Biology Wound Healing Humans Machine Learning 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, ...
Single-Cell Analysis Algorithms Mice Animals Cluster Analysis Gene Expression Profiling Transcriptome Humans Neural Networks, Computer
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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...
Gene Expression Regulation, Neoplastic Ferroptosis Pituitary Neoplasms Craniopharyngioma Biomarkers, Tumor Humans Male Machine Learning Gene Expression Profiling Female Transcriptome
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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...
Humans MicroRNAs Machine Learning Gene Expression Profiling Gene Expression Regulation Biomarkers Transcriptome Thioredoxins Asthma Computational Biology Severity of Illness Index
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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...
Proportional Hazards Models Middle Aged Anoikis Antineoplastic Agents Gene Expression Profiling Gene Expression Transcriptome Blotting, Western Imatinib Mesylate Aged Breast Neoplasms Machine Learning Tumor Microenvironment Prognosis Biomarkers, Tumor Female Treatment Outcome Real-Time Polymerase Chain Reaction Reproducibility of Results Databases, Genetic Reverse Transcriptase Polymerase Chain Reaction Predictive Value of Tests Immunotherapy Drug Screening Assays, Antitumor Enzyme-Linked Immunosorbent Assay
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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...
Unsupervised Machine Learning Glioblastoma Supervised Machine Learning Biomarkers, Tumor Brain Neoplasms Molecular Docking Simulation Gene Expression Profiling Transcriptome Gene Regulatory Networks Gene Expression Regulation, Neoplastic DNA Methylation Humans
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Analyzing immune cell infiltrates in skeletal muscle of infantile-onset Pompe disease using bioinformatics and machine learning.

Scientific reports Nov 11, 2024
Pompe disease, a severe lysosomal storage disorder, is marked by heart problems, muscle weakness, and respiratory difficulties. This study aimed to identify novel markers for infantile-onset Pompe disease by analyzing key genes and immune cells infil...
Machine Learning Biomarkers Infant Gene Expression Profiling Humans Computational Biology Muscle, Skeletal Glycogen Storage Disease Type II
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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...
Tumor Microenvironment Neoplasms Gene Expression Profiling Transcriptome Humans Sequence Analysis, RNA Gene Expression Regulation, Neoplastic Deep Learning Cell Line, Tumor Single-Cell Analysis RNA-Seq
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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...
Female Pulmonary Disease, Chronic Obstructive Animals Male Humans Machine Learning Mice Disease Models, Animal Epithelial Cells Gelsolin Lung Gene Expression Profiling Transcriptome Gene Regulatory Networks
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Machine Learning-enhanced Signature of Metastasis-related T Cell Marker Genes for Predicting Overall Survival in Malignant Melanoma.

Journal of immunotherapy (Hagerstown, Md. : 1997) Nov 7, 2024
In this study, we aimed to investigate disparities in the tumor immune microenvironment (TME) between primary and metastatic malignant melanoma (MM) using single-cell RNA sequencing (scRNA- seq ) and to identify metastasis-related T cell marker genes...
Nomograms Neoplasm Metastasis Prognosis Female Melanoma Tumor Microenvironment Humans Biomarkers, Tumor Machine Learning T-Lymphocytes Male Gene Expression Profiling
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