Correlated primer sequence table. by MaoMeng Wang (22177417)

“…A gene co-expression network was constructed via the Weighted Gene Co-Expression Network Analysis (WGCNA) algorithm to identify disease-related modules. Differentially expressed genes (DEGs) were identified using the linear models for microarray data (limma) R package (version 3.34.7), followed by functional enrichment analysis using DAVID. …”

DEG-WGCNA overlapping genes dataset. by MaoMeng Wang (22177417)

“…A gene co-expression network was constructed via the Weighted Gene Co-Expression Network Analysis (WGCNA) algorithm to identify disease-related modules. Differentially expressed genes (DEGs) were identified using the linear models for microarray data (limma) R package (version 3.34.7), followed by functional enrichment analysis using DAVID. …”

Risk-stratified KEGG pathway enrichment dataset. by MaoMeng Wang (22177417)

“…A gene co-expression network was constructed via the Weighted Gene Co-Expression Network Analysis (WGCNA) algorithm to identify disease-related modules. Differentially expressed genes (DEGs) were identified using the linear models for microarray data (limma) R package (version 3.34.7), followed by functional enrichment analysis using DAVID. …”

Module-trait correlation heatmap. by MaoMeng Wang (22177417)

“…A gene co-expression network was constructed via the Weighted Gene Co-Expression Network Analysis (WGCNA) algorithm to identify disease-related modules. Differentially expressed genes (DEGs) were identified using the linear models for microarray data (limma) R package (version 3.34.7), followed by functional enrichment analysis using DAVID. …”

Raw expression profile dataset. by MaoMeng Wang (22177417)

“…A gene co-expression network was constructed via the Weighted Gene Co-Expression Network Analysis (WGCNA) algorithm to identify disease-related modules. Differentially expressed genes (DEGs) were identified using the linear models for microarray data (limma) R package (version 3.34.7), followed by functional enrichment analysis using DAVID. …”

Data Sheet 1_Gene-level connections between anxiety disorders, ADHD, and head and neck cancer: insights from a computational biology approach.zip by Meng Lian (502465)

“…Overlapping genes were analyzed through protein-protein interaction (PPI) networks, functional annotations, and literature-based pathway analyses to elucidate shared and unique genetic mechanisms linking these diseases.…”

Supplementary file 1_Exploration of the shared gene signatures and molecular mechanisms between cardioembolic stroke and ischemic stroke.docx by Xuan Wang (55634)

“…</p>Results<p>There were 125 shared up-regulated genes and 2 shared down-regulated between CS and IS, which were mainly involved in immune inflammatory response-related biological functions. The Maximum Clique Centrality algorithm identified 25 core shared genes in the PPI network constructed using the shared genes. …”

Table 2_Exploration of the shared gene signatures and molecular mechanisms between cardioembolic stroke and ischemic stroke.xlsx by Xuan Wang (55634)

“…</p>Results<p>There were 125 shared up-regulated genes and 2 shared down-regulated between CS and IS, which were mainly involved in immune inflammatory response-related biological functions. The Maximum Clique Centrality algorithm identified 25 core shared genes in the PPI network constructed using the shared genes. …”

Table 3_Exploration of the shared gene signatures and molecular mechanisms between cardioembolic stroke and ischemic stroke.xlsx by Xuan Wang (55634)

“…</p>Results<p>There were 125 shared up-regulated genes and 2 shared down-regulated between CS and IS, which were mainly involved in immune inflammatory response-related biological functions. The Maximum Clique Centrality algorithm identified 25 core shared genes in the PPI network constructed using the shared genes. …”

Data Sheet 1_Identification of potential diagnostic markers and molecular mechanisms of asthma and ulcerative colitis based on bioinformatics and machine learning.zip by Chenxuyu Zhang (21362012)

“…Shared genes between asthma and UC were derived by intersecting DEGs with UC-associated modules, followed by functional enrichment and protein-protein interaction (PPI) analysis. …”

Table 1_Exploration of the shared gene signatures and molecular mechanisms between cardioembolic stroke and ischemic stroke.xlsx by Xuan Wang (55634)

“…</p>Results<p>There were 125 shared up-regulated genes and 2 shared down-regulated between CS and IS, which were mainly involved in immune inflammatory response-related biological functions. The Maximum Clique Centrality algorithm identified 25 core shared genes in the PPI network constructed using the shared genes. …”

Data Sheet 2_Identification of potential diagnostic markers and molecular mechanisms of asthma and ulcerative colitis based on bioinformatics and machine learning.zip by Chenxuyu Zhang (21362012)

“…Shared genes between asthma and UC were derived by intersecting DEGs with UC-associated modules, followed by functional enrichment and protein-protein interaction (PPI) analysis. …”

Data Sheet 1_Association of microtubule-based processes gene expression with immune microenvironment and its predictive value for drug response in oestrogen receptor-positive breas... by Zhenfeng Huang (836949)

“…Western blotting was used to measure protein levels in breast cancer cell lines. Immunohistochemical staining was used to assess protein expression in paraffin-embedded tissues, and Kaplan–Meier survival curves were generated to evaluate survival differences between the high- and low-expression groups of key genes. …”

Image 1_Exploring the role of mitochondrial metabolism and immune infiltration in myocardial infarction: novel insights from bioinformatics and experimental validation.tif by Jingyi Hou (698975)

“…A protein-protein interaction (PPI) network of mitoDEGs was constructed, and hub mitoDEGs associated with MI were identified using CytoHubba and molecular complex detection (MCODE) algorithms. …”

Image 3_Identification of diagnostic hub genes related to energy metabolism in idiopathic pulmonary fibrosis.tif by S. Zhao (1466308)

“…Subsequent analyses included functional enrichment (GO/KEGG), protein-protein interaction network, and mRNA-miRNA, mRNA-transcription factor interaction networks. …”

Table1_Identification of key genes and immune infiltration of diabetic peripheral neuropathy in mice and humans based on bioinformatics analysis.docx by Yumin Zhang (1534168)

“…The differentially expressed genes (DEGs) were selected and further analyzed by using Gene Ontology, Kyoto Encyclopedia of Genes and Genomes enrichment analysis, and Gene Set Enrichment Analysis (GSEA) to find the shared key pathway. Protein–protein interaction networks were built in shared mouse and human DEGs. …”

Table 5_Identification of diagnostic hub genes related to energy metabolism in idiopathic pulmonary fibrosis.docx by S. Zhao (1466308)

“…Subsequent analyses included functional enrichment (GO/KEGG), protein-protein interaction network, and mRNA-miRNA, mRNA-transcription factor interaction networks. …”

Table 4_Identification of diagnostic hub genes related to energy metabolism in idiopathic pulmonary fibrosis.docx by S. Zhao (1466308)

“…Subsequent analyses included functional enrichment (GO/KEGG), protein-protein interaction network, and mRNA-miRNA, mRNA-transcription factor interaction networks. …”

Table 2_Identification of diagnostic hub genes related to energy metabolism in idiopathic pulmonary fibrosis.csv by S. Zhao (1466308)

“…Subsequent analyses included functional enrichment (GO/KEGG), protein-protein interaction network, and mRNA-miRNA, mRNA-transcription factor interaction networks. …”

Table 1_Identification of diagnostic hub genes related to energy metabolism in idiopathic pulmonary fibrosis.docx by S. Zhao (1466308)

“…Subsequent analyses included functional enrichment (GO/KEGG), protein-protein interaction network, and mRNA-miRNA, mRNA-transcription factor interaction networks. …”