AIMC Topic: Gene Regulatory Networks

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MultiSC: a deep learning pipeline for analyzing multiomics single-cell data.

Briefings in bioinformatics Sep 23, 2024
Single-cell technologies enable researchers to investigate cell functions at an individual cell level and study cellular processes with higher resolution. Several multi-omics single-cell sequencing techniques have been developed to explore various as...
Gene Regulatory Networks Computational Biology Multiomics Transcription Factors Humans Deep Learning Single-Cell Analysis
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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).
Male Gene Expression Profiling Transcriptome Algorithms Retrospective Studies Female Databases, Genetic Fatty Acids Hypertension, Pulmonary Pulmonary Arterial Hypertension ROC Curve Gene Regulatory Networks Computational Biology Humans Machine Learning
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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...
Machine Learning Gene Expression Profiling Gene Regulatory Networks Computational Biology Humans Atherosclerosis
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Combined bioinformatics and machine learning methodologies reveal prognosis-related ceRNA network and propose ABCA8, CAT, and CXCL12 as independent protective factors against osteosarcoma.

Advances in clinical and experimental medicine : official organ Wroclaw Medical University Aug 1, 2024
BACKGROUND: Aberrant circular RNA (circRNA) acts as an oncogene or suppressor during neoplasm initiation and development. However, the functions of most circRNAs in osteosarcoma (OS) remain unclear.
Gene Regulatory Networks Computational Biology RNA, Messenger Machine Learning Prognosis Biomarkers, Tumor MicroRNAs Chemokine CXCL12 ATP-Binding Cassette Transporters Gene Expression Regulation, Neoplastic Osteosarcoma Bone Neoplasms RNA, Circular Protective Factors RNA, Competitive Endogenous Humans
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A genome-scale deep learning model to predict gene expression changes of genetic perturbations from multiplex biological networks.

Briefings in bioinformatics Jul 25, 2024
Systematic characterization of biological effects to genetic perturbation is essential to the application of molecular biology and biomedicine. However, the experimental exhaustion of genetic perturbations on the genome-wide scale is challenging. Her...
Computational Biology Gene Expression Regulation RNA Interference Gene Expression Profiling Deep Learning Gene Regulatory Networks Humans
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Reinventing gene expression connectivity through regulatory and spatial structural empowerment via principal node aggregation graph neural network.

Nucleic acids research Jul 22, 2024
The intricacies of the human genome, manifested as a complex network of genes, transcend conventional representations in text or numerical matrices. The intricate gene-to-gene relationships inherent in this complexity find a more suitable depiction i...
Genome, Human Humans Histone Code Neural Networks, Computer Gene Regulatory Networks Algorithms Transcription Factors Protein Interaction Maps Gene Expression Regulation
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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...
Humans Single-Cell Analysis Sequence Analysis, RNA Neural Networks, Computer Gene Expression Profiling Gene Regulatory Networks Transcription Factors Algorithms Transcriptome Computational Biology Deep Learning
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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...
Humans Machine Learning Algorithms Chronic Disease Oxidative Stress Rhinosinusitis Biomarkers Gene Regulatory Networks Gene Expression Profiling Transcriptome Nasal Polyps
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DeepGRNCS: deep learning-based framework for jointly inferring gene regulatory networks across cell subpopulations.

Briefings in bioinformatics May 23, 2024
Inferring gene regulatory networks (GRNs) allows us to obtain a deeper understanding of cellular function and disease pathogenesis. Recent advances in single-cell RNA sequencing (scRNA-seq) technology have improved the accuracy of GRN inference. Howe...
Sequence Analysis, RNA RNA-Seq Humans Gene Regulatory Networks Transcription Factors Deep Learning Computational Biology Single-Cell Analysis
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Inference of gene regulatory networks based on directed graph convolutional networks.

Briefings in bioinformatics May 23, 2024
Inferring gene regulatory network (GRN) is one of the important challenges in systems biology, and many outstanding computational methods have been proposed; however there remains some challenges especially in real datasets. In this study, we propose...
Computational Biology Humans Neural Networks, Computer Escherichia coli Algorithms Urinary Bladder Neoplasms Gene Regulatory Networks
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