Image 2_Analysis and validation of necroptosis-related diagnostic biomarkers associated with immune infiltration in bronchopulmonary dysplasia.jpg by Haixia Tu (15277372)

“…We identified the biological functions and pathways of DE-NRGs. RF (random forest) and LASSO (least absolute shrinkage and selection operator) algorithms were applied to identify hub genes. …”

Table 2_Identification of regulatory cell death-related genes during MASH progression using bioinformatics analysis and machine learning strategies.xlsx by Zhiqiang Lin (747094)

“…A total of 101 combinations of 10 machine learning algorithms were employed to screen for characteristic RCD-related differentially expressed genes (DEGs) that reflect the progression of MASH. …”

Table 1_Identification of regulatory cell death-related genes during MASH progression using bioinformatics analysis and machine learning strategies.xlsx by Zhiqiang Lin (747094)

“…A total of 101 combinations of 10 machine learning algorithms were employed to screen for characteristic RCD-related differentially expressed genes (DEGs) that reflect the progression of MASH. …”

Table 5_Integrated analysis of stem cell-related genes shared between type 2 diabetes mellitus and sepsis.xlsx by Yubo Wang (556762)

“…The stem-cell-related biomarkers were discovered through combining functional similarity analysis, machine learning algorithms, and receiver operating characteristic (ROC) curves. …”

Data Sheet 1_Integrated analysis of stem cell-related genes shared between type 2 diabetes mellitus and sepsis.docx by Yubo Wang (556762)

“…The stem-cell-related biomarkers were discovered through combining functional similarity analysis, machine learning algorithms, and receiver operating characteristic (ROC) curves. …”

Table 7_Integrated analysis of stem cell-related genes shared between type 2 diabetes mellitus and sepsis.xlsx by Yubo Wang (556762)

“…The stem-cell-related biomarkers were discovered through combining functional similarity analysis, machine learning algorithms, and receiver operating characteristic (ROC) curves. …”

Table 4_Integrated analysis of stem cell-related genes shared between type 2 diabetes mellitus and sepsis.xlsx by Yubo Wang (556762)

“…The stem-cell-related biomarkers were discovered through combining functional similarity analysis, machine learning algorithms, and receiver operating characteristic (ROC) curves. …”

Table 1_Integrated analysis of stem cell-related genes shared between type 2 diabetes mellitus and sepsis.xlsx by Yubo Wang (556762)

“…The stem-cell-related biomarkers were discovered through combining functional similarity analysis, machine learning algorithms, and receiver operating characteristic (ROC) curves. …”

Table 3_Integrated analysis of stem cell-related genes shared between type 2 diabetes mellitus and sepsis.xlsx by Yubo Wang (556762)

“…The stem-cell-related biomarkers were discovered through combining functional similarity analysis, machine learning algorithms, and receiver operating characteristic (ROC) curves. …”

Table 2_Integrated analysis of stem cell-related genes shared between type 2 diabetes mellitus and sepsis.xlsx by Yubo Wang (556762)

“…The stem-cell-related biomarkers were discovered through combining functional similarity analysis, machine learning algorithms, and receiver operating characteristic (ROC) curves. …”

Table 6_Integrated analysis of stem cell-related genes shared between type 2 diabetes mellitus and sepsis.docx by Yubo Wang (556762)

“…The stem-cell-related biomarkers were discovered through combining functional similarity analysis, machine learning algorithms, and receiver operating characteristic (ROC) curves. …”

Data Sheet 1_Novel diagnostic biomarkers associated with macrophage-microglia in spinal cord injury.pdf by Manyi Zheng (22221913)

“…From 200 genes associated with critical WGCNA modules, three hub genes, including EMP3, GNGT2, and SGPL1, were identified through four ML algorithms as differentially expressed before and after injury. …”

Table 4_Novel diagnostic biomarkers associated with macrophage-microglia in spinal cord injury.xlsx by Manyi Zheng (22221913)

“…From 200 genes associated with critical WGCNA modules, three hub genes, including EMP3, GNGT2, and SGPL1, were identified through four ML algorithms as differentially expressed before and after injury. …”

Table 1_Novel diagnostic biomarkers associated with macrophage-microglia in spinal cord injury.xlsx by Manyi Zheng (22221913)

“…From 200 genes associated with critical WGCNA modules, three hub genes, including EMP3, GNGT2, and SGPL1, were identified through four ML algorithms as differentially expressed before and after injury. …”

Data Sheet 2_Novel diagnostic biomarkers associated with macrophage-microglia in spinal cord injury.pdf by Manyi Zheng (22221913)

“…From 200 genes associated with critical WGCNA modules, three hub genes, including EMP3, GNGT2, and SGPL1, were identified through four ML algorithms as differentially expressed before and after injury. …”

Supplementary file 1_Novel diagnostic biomarkers associated with macrophage-microglia in spinal cord injury.xlsx by Manyi Zheng (22221913)

“…From 200 genes associated with critical WGCNA modules, three hub genes, including EMP3, GNGT2, and SGPL1, were identified through four ML algorithms as differentially expressed before and after injury. …”

Table 2_Novel diagnostic biomarkers associated with macrophage-microglia in spinal cord injury.xlsx by Manyi Zheng (22221913)

“…From 200 genes associated with critical WGCNA modules, three hub genes, including EMP3, GNGT2, and SGPL1, were identified through four ML algorithms as differentially expressed before and after injury. …”

Supplementary file 2_Novel diagnostic biomarkers associated with macrophage-microglia in spinal cord injury.xlsx by Manyi Zheng (22221913)

“…From 200 genes associated with critical WGCNA modules, three hub genes, including EMP3, GNGT2, and SGPL1, were identified through four ML algorithms as differentially expressed before and after injury. …”

Table 3_Novel diagnostic biomarkers associated with macrophage-microglia in spinal cord injury.xlsx by Manyi Zheng (22221913)

“…From 200 genes associated with critical WGCNA modules, three hub genes, including EMP3, GNGT2, and SGPL1, were identified through four ML algorithms as differentially expressed before and after injury. …”

Integrative analysis of mitochondrial and immune pathways in diabetic kidney disease: identification of AASS and CASP3 as key predictors and therapeutic targets by Xinxin Yu (528120)

“…Experimental validation was performed using a DKD rat model.</p> <p>WGCNA revealed significant gene modules associated with immune responses and mitochondrial functions. …”