AIMC Topic: Gene Expression Profiling

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Machine Learning Diagnostic Model for Hepatocellular Carcinoma Based on Liquid-Liquid Phase Separation and Ferroptosis-Related Genes.

The Turkish journal of gastroenterology : the official journal of Turkish Society of Gastroenterology Oct 7, 2024
BACKGROUND/AIMS: Hepatocellular carcinoma (HCC) represents a primary liver malignancy with a multifaceted molecular landscape. The interplay between liquid-liquid phase separation (LLPS) and ferroptosis-a regulated form of cell death-has garnered int...
Machine Learning Prognosis Gene Expression Profiling Humans Membrane Proteins Ferroptosis Phase Separation GTP Phosphohydrolases Liver Neoplasms Carcinoma, Hepatocellular Gene Expression Regulation, Neoplastic
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Robust self-supervised learning strategy to tackle the inherent sparsity in single-cell RNA-seq data.

Briefings in bioinformatics Sep 23, 2024
Single-cell RNA sequencing (scRNA-seq) is a powerful tool for elucidating cellular heterogeneity and tissue function in various biological contexts. However, the sparsity in scRNA-seq data limits the accuracy of cell type annotation and transcriptomi...
Humans Algorithms Gene Expression Profiling Single-Cell Analysis RNA-Seq Single-Cell Gene Expression Analysis Computational Biology Sequence Analysis, RNA Supervised Machine Learning
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scDTL: enhancing single-cell RNA-seq imputation through deep transfer learning with bulk cell information.

Briefings in bioinformatics Sep 23, 2024
The increasing single-cell RNA sequencing (scRNA-seq) data enable researchers to explore cellular heterogeneity and gene expression profiles, offering a high-resolution view of the transcriptome at the single-cell level. However, the dropout events, ...
Humans Algorithms Gene Expression Profiling RNA-Seq Sequence Analysis, RNA Transcriptome Single-Cell Gene Expression Analysis Deep Learning Computational Biology Single-Cell Analysis
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Deep contrastive learning for predicting cancer prognosis using gene expression values.

Briefings in bioinformatics Sep 23, 2024
Recent advancements in image classification have demonstrated that contrastive learning (CL) can aid in further learning tasks by acquiring good feature representation from a limited number of data samples. In this paper, we applied CL to tumor trans...
Gene Expression Profiling Transcriptome Deep Learning ROC Curve Computational Biology Gene Expression Regulation, Neoplastic Biomarkers, Tumor Male Neoplasms Humans Prognosis
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Gene expression prediction from histology images via hypergraph neural networks.

Briefings in bioinformatics Sep 23, 2024
Spatial transcriptomics reveals the spatial distribution of genes in complex tissues, providing crucial insights into biological processes, disease mechanisms, and drug development. The prediction of gene expression based on cost-effective histology ...
Computational Biology Neoplasms Gene Expression Profiling Image Processing, Computer-Assisted Humans Neural Networks, Computer Algorithms
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An initial game-theoretic assessment of enhanced tissue preparation and imaging protocols for improved deep learning inference of spatial transcriptomics from tissue morphology.

Briefings in bioinformatics Sep 23, 2024
The application of deep learning to spatial transcriptomics (ST) can reveal relationships between gene expression and tissue architecture. Prior work has demonstrated that inferring gene expression from tissue histomorphology can discern these spatia...
Tissues Humans Gene Expression Profiling Deep Learning Biostatistics Game Theory
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Identification of diagnostic biomarkers and immune cell profiles associated with COPD integrated bioinformatics and machine learning.

Journal of cellular and molecular medicine Sep 1, 2024
This retrospective transcriptomic study leveraged bioinformatics and machine learning algorithms to identify novel gene biomarkers and explore immune cell infiltration profiles associated with chronic obstructive pulmonary disease (COPD). Utilizing a...
GTP-Binding Protein alpha Subunits, Gs Adenylyl Cyclases Computational Biology Killer Cells, Natural Chromogranins Aged Pulmonary Disease, Chronic Obstructive Male Middle Aged Gene Expression Profiling Transcriptome Biomarkers Retrospective Studies Humans Female Machine Learning
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Identification of fatty acid metabolism signature genes in patients with pulmonary arterial hypertension using WGCNA and machine learning.

The Journal of international medical research Sep 1, 2024
OBJECTIVE: To investigate the signature genes of fatty acid metabolism and their association with immune cells in pulmonary arterial hypertension (PAH).
Humans Female Male Gene Expression Profiling Machine Learning Algorithms Retrospective Studies Hypertension, Pulmonary Pulmonary Arterial Hypertension Computational Biology Databases, Genetic Fatty Acids Transcriptome ROC Curve Gene Regulatory Networks
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Predicting spatially resolved gene expression via tissue morphology using adaptive spatial GNNs.

Bioinformatics (Oxford, England) Sep 1, 2024
MOTIVATION: Spatial transcriptomics technologies, which generate a spatial map of gene activity, can deepen the understanding of tissue architecture and its molecular underpinnings in health and disease. However, the high cost makes these technologie...
Gene Expression Profiling Transcriptome Humans Neural Networks, Computer Female Breast Neoplasms
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Bioinformatics and machine learning approaches reveal key genes and underlying molecular mechanisms of atherosclerosis: A review.

Medicine Aug 2, 2024
Atherosclerosis (AS) causes thickening and hardening of the arterial wall due to accumulation of extracellular matrix, cholesterol, and cells. In this study, we used comprehensive bioinformatics tools and machine learning approaches to explore key ge...
Gene Regulatory Networks Humans Computational Biology Machine Learning Atherosclerosis Gene Expression Profiling
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