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Identification of novel inflammatory response-related biomarkers in patients with ischemic stroke based on WGCNA and machine learning.

Chenyi Huang | Dengxuan Wu | Guifen Yang | Chuchu Huang | Li Li
European journal of medical research | 2025

Ischemic stroke (IS) is one of the most common causes of disability in adults worldwide. This study aimed to identify key genes related to the inflammatory response to provide insights into the mechanisms and management of IS.

Pubmed ID: 40119397

Research resources used in this publication

None found

Antibodies used in this publication

None found

Associated grants

  • Agency: the Project of Administration of Traditional Chinese Medicine of Zhejiang Province of China,
    Id: 2025ZR089

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This is a list of tools and resources that we have found mentioned in this publication.


Gene Set Enrichment Analysis (tool)

RRID:SCR_003199

Software package for interpreting gene expression data. Used for interpretation of a large-scale experiment by identifying pathways and processes.

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NCBI Epigenomics (tool)

RRID:SCR_006151

THIS RESOURCE IS NO LONGER IN SERVICE, documented on January 19, 2022.

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LIMMA (tool)

RRID:SCR_010943

Software package for the analysis of gene expression microarray data, especially the use of linear models for analyzing designed experiments and the assessment of differential expression.

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KEGG (tool)

RRID:SCR_012773

Integrated database resource consisting of 16 main databases, broadly categorized into systems information, genomic information, and chemical information. In particular, gene catalogs in completely sequenced genomes are linked to higher-level systemic functions of cell, organism, and ecosystem. Analysis tools are also available. KEGG may be used as reference knowledge base for biological interpretation of large-scale datasets generated by sequencing and other high-throughput experimental technologies.

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ggplot2 (tool)

RRID:SCR_014601

Open source software package for statistical programming language R to create plots based on grammar of graphics. Used for data visualization to break up graphs into semantic components such as scales and layers.

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