AIMC Topic: Gene Expression Profiling
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A stemness-based signature with inspiring indications in discriminating the prognosis, immune response, and somatic mutation of endometrial cancer patients revealed by machine learning.
Aging
Jul 30, 2024
Endometrial cancer (EC) is a fatal gynecologic tumor. Bioinformatic tools are increasingly developed to screen out molecular targets related to EC. Our study aimed to identify stemness-related prognostic biomarkers for new therapeutic strategies in E...
Detecting differentially expressed genes from RNA-seq data using fuzzy clustering.
The international journal of biostatistics
Jul 29, 2024
A two-group comparison test is generally performed on RNA sequencing data to detect differentially expressed genes (DEGs). However, the accuracy of this method is low due to the small sample size. To address this, we propose a method using fuzzy clus...
Utilizing machine learning and bioinformatics analysis to identify drought-responsive genes affecting yield in foxtail millet.
International journal of biological macromolecules
Jul 29, 2024
Drought stress is a major constraint on crop development, potentially causing huge yield losses and threatening global food security. Improving Crop's stress tolerance is usually associated with a yield penalty. One way to balance yield and stress to...
Single-cell hdWGCNA reveals metastatic protective macrophages and development of deep learning model in uveal melanoma.
Journal of translational medicine
Jul 29, 2024
BACKGROUND: Although there has been some progress in the treatment of primary uveal melanoma (UVM), distant metastasis remains the leading cause of death in patients. Monitoring, staging, and treatment of metastatic disease have not yet reached conse...
Identification of diagnostic genes and drug prediction in metabolic syndrome-associated rheumatoid arthritis by integrated bioinformatics analysis, machine learning, and molecular docking.
Frontiers in immunology
Jul 29, 2024
BACKGROUND: Interactions between the immune and metabolic systems may play a crucial role in the pathogenesis of metabolic syndrome-associated rheumatoid arthritis (MetS-RA). The purpose of this study was to discover candidate biomarkers for the diag...
RACGAP1 is a pivotal gene in lung adenocarcinoma-associated membranous nephropathy: Based on comprehensive bioinformatics analysis and machine learning.
International immunopharmacology
Jul 27, 2024
BACKGROUND: This study performs a detailed bioinformatics and machine learning analysis to investigate the genetic foundations of membranous nephropathy (MN) in lung adenocarcinoma (LUAD).
Elucidating Microglial Heterogeneity and Functions in Alzheimer's Disease Using Single-cell Analysis and Convolutional Neural Network Disease Model Construction.
Scientific reports
Jul 27, 2024
In this study, we conducted an in-depth exploration of Alzheimer's Disease (AD) by integrating state-of-the-art methodologies, including single-cell RNA sequencing (scRNA-seq), weighted gene co-expression network analysis (WGCNA), and a convolutional...
Identification of and as novel diagnostic biomarkers for latent tuberculosis infection using machine learning strategies and experimental verification.
Annals of medicine
Jul 25, 2024
BACKGROUND: Current diagnostic methods cannot effectively distinguish between latent tuberculosis infection (LTBI) and active tuberculosis (ATB). This study aims to explore novel non-invasive diagnostic biomarkers for LTBI and to elucidate possible m...
Potential Shared Mitochondrial-Related Gene Signatures and Molecular Mechanisms Between Polycystic Ovary Syndrome (PCOS) and Major Depressive Disorder (MDD): Evidence from Transcriptome Data and Machine Learning.
Molecular biotechnology
Jul 24, 2024
Polycystic ovary syndrome (PCOS) is strongly associated with major depressive disorder (MDD), but the shared pathophysiological mechanisms between them are ambiguous, and the aim of this study was to explore the shared genetic features and associated...
Transcriptionally Conditional Recurrent Neural Network for De Novo Drug Design.
Journal of chemical information and modeling
Jul 24, 2024
Computational molecular generation methods that generate chemical structures from gene expression profiles have been actively developed for de novo drug design. However, most omics-based methods involve complex models consisting of multiple neural ne...
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