AIMC Topic: Gene Expression Profiling

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Identification of regulatory cell death-related genes during MASH progression using bioinformatics analysis and machine learning strategies.

Frontiers in immunology Jan 1, 2025
BACKGROUND: Metabolic dysfunction-associated steatohepatitis (MASH) is becoming increasingly prevalent. Regulated cell death (RCD) has emerged as a significant disease phenotype and may act as a marker for liver fibrosis. The present study aimed to i...
Liver Cirrhosis Databases, Genetic Disease Models, Animal Transcriptome Mice Computational Biology Gene Ontology Non-alcoholic Fatty Liver Disease Cell Death Gene Expression Regulation Humans Disease Progression Gene Expression Profiling Machine Learning Animals
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Identification and validation of immune-related and inflammation-related genes in endometriosis.

Frontiers in endocrinology Jan 1, 2025
AIM: Endometriosis is characterized by immune evasion and progressive inflammation. This study aimed to identify key genes related to immune and inflammation in endometriosis.
Humans Machine Learning Female Gene Expression Profiling Inflammation Endometriosis
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An efficient leukemia prediction method using machine learning and deep learning with selected features.

PloS one Jan 1, 2025
Leukemia is a serious problem affecting both children and adults, leading to death if left untreated. Leukemia is a kind of blood cancer described by the rapid proliferation of abnormal blood cells. An early, trustworthy, and precise identification o...
Databases, Genetic Leukemia Machine Learning Gene Expression Profiling Deep Learning Humans
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Mechanistic role of pyroptosis in Kawasaki disease: An integrative bioinformatics analysis of immune dysregulation, machine learning-based biomarker discovery, WGCNA, and drug repurposing insights.

PloS one Jan 1, 2025
Kawasaki disease (KD) is an acute vasculitis that primarily affects children under five and is a leading cause of acquired heart disease in this age group. Despite the standard treatment with intravenous immunoglobulin (IVIG), approximately 10-20% of...
Machine Learning Biomarkers Molecular Docking Simulation Gene Expression Profiling Humans Mucocutaneous Lymph Node Syndrome Drug Repositioning Pyroptosis Myeloid Differentiation Factor 88 Transcriptome Gene Regulatory Networks Computational Biology
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Development of an immune-related gene signature applying Ridge method for improving immunotherapy responses and clinical outcomes in lung adenocarcinoma.

PeerJ Jan 1, 2025
BACKGROUND: Lung adenocarcinoma (LUAD) is a major cause of cancer mortality. Considering the critical role of tumor infiltrating lymphocytes in effective immunotherapy, this study was designed to screen molecular markers related to tumor infiltrating...
Lymphocytes, Tumor-Infiltrating Adenocarcinoma of Lung Biomarkers, Tumor Male Immunotherapy Transcriptome Gene Expression Profiling Humans Gene Expression Regulation, Neoplastic Lung Neoplasms Prognosis Female
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Applying AI/ML for Analyzing Gene Expression Patterns.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2025
Artificial intelligence (AI) and machine learning (ML) have advanced in several areas and fields of life; however, its progress in the field of genomics is not matching the levels others have achieved. Challenges include but are not limited to the ha...
Genomics Gene Expression Profiling Computational Biology Humans Transcriptome Artificial Intelligence RNA-Seq Machine Learning
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Identification and Immunological Characterization of Cuproptosis Related Genes in Preeclampsia Using Bioinformatics Analysis and Machine Learning.

Journal of clinical hypertension (Greenwich, Conn.) Jan 1, 2025
Preeclampsia (PE) is a pregnancy-specific disorder characterized by an unclearly understood pathogenesis and poses a great threat to maternal and fetal safety. Cuproptosis, a novel form of cellular death, has been implicated in the advancement of var...
Databases, Genetic Protein Interaction Maps Humans Gene Regulatory Networks Pre-Eclampsia Female Machine Learning Computational Biology Gene Ontology Gene Expression Profiling Pregnancy
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Diagnostic Power of MicroRNAs in Melanoma: Integrating Machine Learning for Enhanced Accuracy and Pathway Analysis.

Journal of cellular and molecular medicine Jan 1, 2025
This study identifies microRNAs (miRNAs) with significant discriminatory power in distinguishing melanoma from nevus, notably hsa-miR-26a and hsa-miR-211, which have exhibited diagnostic potential with accuracy of 81% and 78% respectively. To enhance...
Gene Expression Regulation, Neoplastic Signal Transduction Biomarkers, Tumor MicroRNAs Gene Expression Profiling Humans Protein Interaction Maps Gene Regulatory Networks Machine Learning Melanoma
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Immunoinfiltration Analysis of Mitochondrial Damage-Related Genes in Lung Adenocarcinoma and Construction of a Classification and Prognostic Model Integrated With WGCNA and Machine Learning Algorithms.

Cancer medicine Jan 1, 2025
BACKGROUND: Lung adenocarcinoma (LUAD) exhibits molecular heterogeneity, with mitochondrial damage affecting progression. The relationship between mitochondrial damage and immune infiltration, and Weighted Gene Co-expression Network Analysis (WGCNA)-...
Biomarkers, Tumor Humans Mitochondria Gene Expression Regulation, Neoplastic Lung Neoplasms Adenocarcinoma of Lung Machine Learning Gene Expression Profiling Databases, Genetic Gene Regulatory Networks Computational Biology Prognosis
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TPD52 as a Therapeutic Target Identified by Machine Learning Shapes the Immune Microenvironment in Breast Cancer.

Journal of cellular and molecular medicine Jan 1, 2025
Breast cancer (BRCA) is one of the most common malignancies and a leading cause of cancer-related mortality among women globally. Despite advances in diagnosis and treatment, the heterogeneity of BRCA presents significant challenges for effective man...
Breast Neoplasms Gene Expression Regulation, Neoplastic Tumor Microenvironment Neoplasm Proteins Biomarkers, Tumor Machine Learning Prognosis Single-Cell Analysis Female Computational Biology Gene Expression Profiling Humans Cell Line, Tumor
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