Data_Sheet_3_Comprehensive analysis of the diagnostic and therapeutic value, immune infiltration, and drug treatment mechanisms of GTSE1 in lung adenocarcinoma.docx by Guanqiang Yan (18472116)

“…GTSE1 expression emerged as an independent predictive factor in both univariate and multivariate Cox regression analyses. …”

Table 2_Integrative machine learning and bioinformatics analysis to identify cellular senescence-related genes and potential therapeutic targets in ulcerative colitis and colorecta... by Tianle Xue (21462608)

“…The diagnostic performance of the candidate genes was evaluated using receiver operating characteristic (ROC) analyses in both training and validation cohorts. In addition, immune cell infiltration, protein–protein interaction (PPI) networks, and drug enrichment analyses—including molecular docking—were performed to further elucidate the biological functions and therapeutic potentials of the identified genes.…”

Data_Sheet_1_Comprehensive analysis of the diagnostic and therapeutic value, immune infiltration, and drug treatment mechanisms of GTSE1 in lung adenocarcinoma.docx by Guanqiang Yan (18472116)

“…GTSE1 expression emerged as an independent predictive factor in both univariate and multivariate Cox regression analyses. …”

Table 3_Integrative machine learning and bioinformatics analysis to identify cellular senescence-related genes and potential therapeutic targets in ulcerative colitis and colorecta... by Tianle Xue (21462608)

“…The diagnostic performance of the candidate genes was evaluated using receiver operating characteristic (ROC) analyses in both training and validation cohorts. In addition, immune cell infiltration, protein–protein interaction (PPI) networks, and drug enrichment analyses—including molecular docking—were performed to further elucidate the biological functions and therapeutic potentials of the identified genes.…”

Data Sheet 1_Diagnostic lncRNA biomarkers and immune-related ceRNA networks for osteonecrosis of the femoral head in metabolic syndrome identified by plasma RNA sequencing and mach... by Haoyan Sun (22172911)

“…The MetS dataset from the Gene Expression Omnibus (GEO) was integrated, and weighted gene co-expression network analysis (WGCNA), functional enrichment, protein-protein interaction (PPI) network analysis, MCODE, CytoHubba-MCC, and random forest (RF) algorithms were employed to identify hub mRNAs and their associated lncRNAs. …”

Table 1_Demethylase FTO mediates m6A modification of ENST00000619282 to promote apoptosis escape in rheumatoid arthritis and the intervention effect of Xinfeng Capsule.docx by Fanfan Wang (1669474)

“…</p>Methods<p>A retrospective analysis was conducted on 1603 RA patients using association rule mining and random walk algorithms to evaluate the efficacy of XFC. The proliferation and apoptosis of co-cultured RA-FLS were assessed using CCK-8, flow cytometry (FCM), and molecular biology techniques. …”

DataSheet1_Mitochondrial-related genes as prognostic and metastatic markers in breast cancer: insights from comprehensive analysis and clinical models.docx by Yutong Fang (16621143)

“…Contemporary research progressively suggests that mitochondrial dysfunction plays a pivotal role in both the inception and advancement of BC. However, investigations delving into the correlation between mitochondrial-related genes (MRGs) and the prognosis and metastasis of BC are still infrequent.…”

Table1_Mitochondrial-related genes as prognostic and metastatic markers in breast cancer: insights from comprehensive analysis and clinical models.xlsx by Yutong Fang (16621143)

“…Contemporary research progressively suggests that mitochondrial dysfunction plays a pivotal role in both the inception and advancement of BC. However, investigations delving into the correlation between mitochondrial-related genes (MRGs) and the prognosis and metastasis of BC are still infrequent.…”

Raw LC-MS/MS and RNA-Seq Mitochondria data by Stefano Martellucci (16284377)

“…The missing values were imputed with the minimum intensity value for each specific data set; (b) for samples expressed in both scLRP1+/+ and scLRP1-/- tissue, the filtering process required 2 or more proteins to be detected in both scLRP1+/+ and scLRP1-/- samples. …”

<b>Figures for Protein-Protein interaction (PPI) network of differentially acetylated proteins</b><b> </b><b>by Aspirin during differentiation of THP-1 cell towards macrophage</b> by Zi-Hui Ma (14118552)

“…The protein-protein interaction (PPI) networks were generated using STRING (H. sapiens; confidence score > 0.7) and visualized in Cytoscape 3.2.1. to elucidate how Aspirin-driven acetylated proteins functionally coordinate within cellular systems. The PPI network was further analyzed to identify densely interconnected functional clusters/modules using topological clustering algorithms. …”

<b>Protein-Protein interaction (PPI) network of differentially acetylated proteins</b><b> by Aspirin during differentiation of THP-1 cell towards macrophage</b> by Li Xing (21105170)

“…The protein-protein interaction (PPI) networks were generated using STRING (H. sapiens; confidence score > 0.7) and visualized in Cytoscape 3.2.1. to elucidate how Aspirin-driven acetylated proteins functionally coordinate within cellular systems. The PPI network was further analyzed to identify densely interconnected functional clusters/modules using topological clustering algorithms. …”

Table 1_Machine learning identifies PYGM as a macrophage polarization–linked metabolic biomarker in rectal cancer prognosis.docx by Chengyuan Xu (4174936)

“…Clinical tissue analyses and functional assays confirmed that PYGM is upregulated in rectal cancer and promotes tumor cell proliferation, migration, and M2 macrophage polarization.…”

Table 3_Exploring common circulating diagnostic biomarkers for sleep disorders and stroke based on machine learning.xlsx by Hanlin Yu (17776399)

“…With WGCNA and machine-learning algorithms analyses, we found that ARL2 is an important common marker for both diseases.…”

Table 1_Exploring common circulating diagnostic biomarkers for sleep disorders and stroke based on machine learning.xlsx by Hanlin Yu (17776399)

“…With WGCNA and machine-learning algorithms analyses, we found that ARL2 is an important common marker for both diseases.…”

Table 4_Exploring common circulating diagnostic biomarkers for sleep disorders and stroke based on machine learning.xlsx by Hanlin Yu (17776399)

“…With WGCNA and machine-learning algorithms analyses, we found that ARL2 is an important common marker for both diseases.…”

Table 2_Exploring common circulating diagnostic biomarkers for sleep disorders and stroke based on machine learning.xlsx by Hanlin Yu (17776399)

“…With WGCNA and machine-learning algorithms analyses, we found that ARL2 is an important common marker for both diseases.…”

Image 1_Exploring common circulating diagnostic biomarkers for sleep disorders and stroke based on machine learning.tif by Hanlin Yu (17776399)

“…With WGCNA and machine-learning algorithms analyses, we found that ARL2 is an important common marker for both diseases.…”

Image 4_Exploring common circulating diagnostic biomarkers for sleep disorders and stroke based on machine learning.tif by Hanlin Yu (17776399)

“…With WGCNA and machine-learning algorithms analyses, we found that ARL2 is an important common marker for both diseases.…”

Image 2_Exploring common circulating diagnostic biomarkers for sleep disorders and stroke based on machine learning.tiff by Hanlin Yu (17776399)

“…With WGCNA and machine-learning algorithms analyses, we found that ARL2 is an important common marker for both diseases.…”

Data Sheet 1_Comprehensive bioinformatics analysis identifies metabolic and immune-related diagnostic biomarkers shared between diabetes and COPD using multi-omics and machine lear... by Qianqian Liang (1521904)

“…</p>Results<p>Cross-analysis identified 186 shared DEGs between diabetes and COPD patients. Functional enrichment results demonstrate that metabolic and immune-related pathways are common features altered in both diabetes and COPD patients. …”