AIMC Topic: Gene Expression Profiling
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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...
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...
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...
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...
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...
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)-...
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...
Unveiling Long Non-coding RNA Networks from Single-Cell Omics Data Through Artificial Intelligence.
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2025
Single-cell omics technologies have revolutionized the study of long non-coding RNAs (lncRNAs), offering unprecedented resolution in elucidating their expression dynamics, cell-type specificity, and associated gene regulatory networks (GRNs). Concurr...
Identification of miR-20a as a Diagnostic and Prognostic Biomarker in Colorectal Cancer: MicroRNA Sequencing and Machine Learning Analysis.
MicroRNA (Shariqah, United Arab Emirates)
Jan 1, 2025
INTRODUCTION: The differential expression of miRNAs, a key regulator in many cell signaling pathways, has been studied in various malignancies and may have an important role in cancer progression, including colorectal cancer (CRC).
Developing a Predictive Model for Metastatic Potential in Pancreatic Neuroendocrine Tumor.
The Journal of clinical endocrinology and metabolism
Dec 18, 2024
CONTEXT: Pancreatic neuroendocrine tumors (PNETs) exhibit a wide range of behavior from localized disease to aggressive metastasis. A comprehensive transcriptomic profile capable of differentiating between these phenotypes remains elusive.
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