AIMC Topic: Gene Expression Profiling

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Integrating machine learning and single-cell analysis to uncover lung adenocarcinoma progression and prognostic biomarkers.

Journal of cellular and molecular medicine Jul 1, 2024
The progression of lung adenocarcinoma (LUAD) from atypical adenomatous hyperplasia (AAH) to invasive adenocarcinoma (IAC) involves a complex evolution of tumour cell clusters, the mechanisms of which remain largely unknown. By integrating single-cel...
Disease Progression Gene Expression Profiling Single-Cell Analysis Lung Neoplasms Prognosis Tumor Microenvironment Biomarkers, Tumor Immunotherapy Gene Expression Regulation, Neoplastic Adenocarcinoma of Lung Humans Machine Learning
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Advancing lung adenocarcinoma prognosis and immunotherapy prediction with a multi-omics consensus machine learning approach.

Journal of cellular and molecular medicine Jul 1, 2024
Lung adenocarcinoma (LUAD) is a tumour characterized by high tumour heterogeneity. Although there are numerous prognostic and immunotherapeutic options available for LUAD, there is a dearth of precise, individualized treatment plans. We integrated mR...
Humans Machine Learning Prognosis Biomarkers, Tumor Multiomics Adenocarcinoma of Lung Gene Expression Regulation, Neoplastic MicroRNAs Gene Expression Profiling Lung Neoplasms Immunotherapy
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SFINN: inferring gene regulatory network from single-cell and spatial transcriptomic data with shared factor neighborhood and integrated neural network.

Bioinformatics (Oxford, England) Jul 1, 2024
MOTIVATION: The rise of single-cell RNA sequencing (scRNA-seq) technology presents new opportunities for constructing detailed cell type-specific gene regulatory networks (GRNs) to study cell heterogeneity. However, challenges caused by noises, techn...
Sequence Analysis, RNA Transcription Factors Single-Cell Analysis Gene Regulatory Networks Humans Computational Biology Transcriptome Neural Networks, Computer Deep Learning Algorithms Gene Expression Profiling
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DeepGSEA: explainable deep gene set enrichment analysis for single-cell transcriptomic data.

Bioinformatics (Oxford, England) Jul 1, 2024
MOTIVATION: Gene set enrichment (GSE) analysis allows for an interpretation of gene expression through pre-defined gene set databases and is a critical step in understanding different phenotypes. With the rapid development of single-cell RNA sequenci...
Humans Neural Networks, Computer Deep Learning Software Computational Biology Gene Expression Profiling Single-Cell Analysis Transcriptome Sequence Analysis, RNA
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Adaptive digital tissue deconvolution.

Bioinformatics (Oxford, England) Jun 28, 2024
MOTIVATION: The inference of cellular compositions from bulk and spatial transcriptomics data increasingly complements data analyses. Multiple computational approaches were suggested and recently, machine learning techniques were developed to systema...
Computational Biology Female Humans Breast Neoplasms Machine Learning Gene Expression Profiling Algorithms Transcriptome
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[Identification of oxidative stress-related biomarkers in chronic rhinosinusitis with nasal polyps using WGCNA combined with machine learning algorithms].

Zhonghua er bi yan hou tou jing wai ke za zhi = Chinese journal of otorhinolaryngology head and neck surgery Jun 7, 2024
To identify diagnostic markers related to oxidative stress in chronic rhinosinusitis with nasal polyps (CRSwNP) by analyzing transcriptome sequencing data, and to investigate their roles in CRSwNP. Utilizing four CRSwNP sequencing datasets, differe...
Rhinosinusitis Gene Regulatory Networks Nasal Polyps Chronic Disease Biomarkers Humans Gene Expression Profiling Machine Learning Transcriptome Algorithms Oxidative Stress
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[Exploration of prognostic models for chronic rhinosinusitis with nasal polyps based on machine learning].

Zhonghua er bi yan hou tou jing wai ke za zhi = Chinese journal of otorhinolaryngology head and neck surgery Jun 7, 2024
To analysis the molecular characteristics of chronic rhinosinusitis with nasal polyps (CRSwNP), to unravel its pathophysiological mechanisms, and to develop a prognostic model capable of effectively predicting postoperative recurrence. The data fro...
Prognosis Gene Expression Profiling ROC Curve Rhinosinusitis Recurrence Nasal Polyps Chronic Disease Humans Machine Learning
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Machine learning-based identification of a cell death-related signature associated with prognosis and immune infiltration in glioma.

Journal of cellular and molecular medicine Jun 1, 2024
Accumulating evidence suggests that a wide variety of cell deaths are deeply involved in cancer immunity. However, their roles in glioma have not been explored. We employed a logistic regression model with the shrinkage regularization operator (LASSO...
Nomograms Glioma Lymphocytes, Tumor-Infiltrating Cell Death Myeloid Differentiation Factor 88 Transcriptome ROC Curve Gene Expression Regulation, Neoplastic Male Middle Aged Gene Expression Profiling Humans Machine Learning Biomarkers, Tumor Brain Neoplasms Prognosis Female
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ctGAN: combined transformation of gene expression and survival data with generative adversarial network.

Briefings in bioinformatics May 23, 2024
Recent studies have extensively used deep learning algorithms to analyze gene expression to predict disease diagnosis, treatment effectiveness, and survival outcomes. Survival analysis studies on diseases with high mortality rates, such as cancer, ar...
Gene Expression Profiling Deep Learning Humans Computational Biology Female Neural Networks, Computer Gene Expression Regulation, Neoplastic Breast Neoplasms Algorithms Survival Analysis Neoplasms
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AITeQ: a machine learning framework for Alzheimer's prediction using a distinctive five-gene signature.

Briefings in bioinformatics May 23, 2024
Neurodegenerative diseases, such as Alzheimer's disease, pose a significant global health challenge with their complex etiology and elusive biomarkers. In this study, we developed the Alzheimer's Identification Tool (AITeQ) using ribonucleic acid-seq...
RNA-Seq Humans Computational Biology Alzheimer Disease Machine Learning Algorithms Gene Expression Profiling Transcriptome
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