AIMC Topic: Gene Expression Profiling

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Combining machine learning with external validation to explore necroptosis and immune response in moyamoya disease.

BMC immunology Feb 13, 2025
Moyamoya disease (MMD) is a rare chronic vascular disease leads to cognitive impairment and stroke with its etiology unknown. The relationship between necroptosis or necroinflammation and MMD pathogenesis was poorly understood. Differentially express...
Humans Machine Learning Gene Regulatory Networks Support Vector Machine Gene Expression Profiling Protein Interaction Maps Necroptosis Immunity Moyamoya Disease
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X-scPAE: An explainable deep learning model for embryonic lineage allocation prediction based on single-cell transcriptomics revealing key genes in embryonic cell development.

Computers in biology and medicine Feb 12, 2025
In single-cell transcriptomics research, accurately predicting cell lineage allocation and identifying differences between lineages are crucial for understanding cell differentiation processes and reducing early pregnancy miscarriages in humans. This...
Gene Expression Profiling Transcriptome Deep Learning Humans Embryonic Development Algorithms Cell Lineage Female Single-Cell Analysis Animals Mice
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A machine learning-based investigation of integrin expression patterns in cancer and metastasis.

Scientific reports Feb 12, 2025
Integrins, a family of transmembrane receptor proteins, are well known to play important roles in cancer development and metastasis. However, a comprehensive understanding of these roles has not been achieved due to the complex relationships between ...
Databases, Genetic Neoplasm Metastasis Integrins Male Neoplasms Gene Expression Profiling Humans Gene Expression Regulation, Neoplastic Machine Learning Female
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A multi-classification deep neural network for cancer type identification from high-dimension, small-sample and imbalanced gene microarray data.

Scientific reports Feb 12, 2025
Gene microarray technology provides an efficient way to diagnose cancer. However, microarray gene expression data face the challenges of high-dimension, small-sample, and multi-class imbalance. The coupling of these challenges leads to inaccurate res...
Oligonucleotide Array Sequence Analysis Gene Expression Profiling Computational Biology Databases, Genetic Algorithms Neoplasms Humans Neural Networks, Computer
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Machine Learning-Driven Identification of Molecular Subgroups in Medulloblastoma via Gene Expression Profiling.

Clinical oncology (Royal College of Radiologists (Great Britain)) Feb 11, 2025
AIMS: Medulloblastoma (MB) is the most prevalent malignant brain tumour in children, characterised by substantial molecular heterogeneity across its subgroups. Accurate classification is pivotal for personalised treatment strategies and prognostic as...
Gene Expression Profiling Child, Preschool Child Support Vector Machine Machine Learning Female Male Cerebellar Neoplasms Humans Medulloblastoma
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Identification of critical biomarkers and immune infiltration in preeclampsia through bioinformatics and machine learning methods.

BMC pregnancy and childbirth Feb 11, 2025
BACKGROUND: Preeclampsia (PE) is a multisystem progressive disease that occurs during pregnancy. Previous studies have shown that the immune system is involved in the placental trophoblast function and the pathological process of uterine vascular rem...
Humans Machine Learning Biomarkers ROC Curve Gene Regulatory Networks Computational Biology Placenta Pregnancy Female Gene Expression Profiling Pre-Eclampsia
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Feature gene selection and functional validation of SH3KBP1 in infantile hemangioma using machine learning.

Biochemical and biophysical research communications Feb 10, 2025
BACKGROUND: Infantile hemangioma (IH) is a prevalent vascular tumor in infancy with a complex pathogenesis that remains unclear. This study aimed to investigate the underlying mechanisms of IH using comprehensive bioinformatics analyses and in vitro ...
Hemangioma Machine Learning Female Computational Biology Male Infant Gene Expression Regulation, Neoplastic MicroRNAs Humans Gene Expression Profiling Adaptor Proteins, Signal Transducing Child, Preschool Gene Regulatory Networks
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Differential gene expression analysis and machine learning identified structural, TFs, cytokine and glycoproteins, including SOX2, TOP2A, SPP1, COL1A1, and TIMP1 as potential drivers of lung cancer.

Biomarkers : biochemical indicators of exposure, response, and susceptibility to chemicals Feb 10, 2025
BACKGROUND: Lung cancer is a primary global health concern, responsible for a considerable portion of cancer-related fatalities worldwide. Understanding its molecular complexities is crucial for identifying potential targets for treatment. The goal i...
Protein Interaction Maps Gene Regulatory Networks Lung Neoplasms Gene Expression Regulation, Neoplastic Machine Learning Humans Biomarkers, Tumor Gene Expression Profiling SOXB1 Transcription Factors Osteopontin Collagen Type I, alpha 1 Chain Poly-ADP-Ribose Binding Proteins Collagen Type I DNA Topoisomerases, Type II Tissue Inhibitor of Metalloproteinase-1
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Galactose-Induced Cataracts in Rats: A Machine Learning Analysis.

International journal of medical sciences Feb 10, 2025
Rat models are widely used to study cataracts due to their cost-effectiveness and prominent physiological and genetic similarities to humans The objective of this study was to identify genes involved in cataractogenesis due to galactose exposure in ...
Transcription Factors Male Disease Models, Animal Humans Gene Expression Profiling Cataract Galactose Lens, Crystalline Machine Learning Rats Gene Expression Regulation Animals
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Analysis and validation of programmed cell death genes associated with spinal cord injury progression based on bioinformatics and machine learning.

International immunopharmacology Feb 9, 2025
BACKGROUND: Spinal cord injury (SCI) is a severe condition affecting the central nervous system. It is marked by a high disability rate and potential for death. Research has demonstrated that programmed cell death (PCD) plays a significant role in th...
Animals Mice Humans Disease Progression Computational Biology Apoptosis Machine Learning Spinal Cord Injuries Gene Expression Profiling Databases, Genetic MicroRNAs Protein Interaction Maps
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