Data Sheet 1_Identification and validation of cellular senescence-related genes and immune cell infiltration characteristics in intervertebral disc degeneration.pdf by Hao Li (31608)

“…A protein–protein interaction (PPI) network was also drawn, and the hub SRDEGs were obtained using 11 different algorithms. Immune infiltration analysis was then performed. …”

Image 1_Exercise-related immune gene signature for hepatocellular carcinoma: machine learning and multi-omics analysis.pdf by Cheng Pu (14791088)

“…Furthermore, we conducted molecular subtyping, qRT-PCR, biological functions, immune infiltration, drug sensitivity, and single cell analyses on EIGPS.…”

Data Sheet 1_Exercise-related immune gene signature for hepatocellular carcinoma: machine learning and multi-omics analysis.xlsx by Cheng Pu (14791088)

“…Furthermore, we conducted molecular subtyping, qRT-PCR, biological functions, immune infiltration, drug sensitivity, and single cell analyses on EIGPS.…”

Table 8_Machine learning-based integration of DCE-MRI radiomics for STAT3 expression prediction and survival stratification in breast cancer.docx by Dong Pan (1835707)

“…A STAT3 predictive model was developed using six machine learning algorithms. Model performance was assessed using receiver operating characteristic (ROC) and related diagnostic statistical indicators.…”

Image 10_Machine learning-based integration of DCE-MRI radiomics for STAT3 expression prediction and survival stratification in breast cancer.tif by Dong Pan (1835707)

“…A STAT3 predictive model was developed using six machine learning algorithms. Model performance was assessed using receiver operating characteristic (ROC) and related diagnostic statistical indicators.…”

Table 2_Machine learning-based integration of DCE-MRI radiomics for STAT3 expression prediction and survival stratification in breast cancer.xlsx by Dong Pan (1835707)

“…A STAT3 predictive model was developed using six machine learning algorithms. Model performance was assessed using receiver operating characteristic (ROC) and related diagnostic statistical indicators.…”

Table 3_Machine learning-based integration of DCE-MRI radiomics for STAT3 expression prediction and survival stratification in breast cancer.docx by Dong Pan (1835707)

“…A STAT3 predictive model was developed using six machine learning algorithms. Model performance was assessed using receiver operating characteristic (ROC) and related diagnostic statistical indicators.…”

Image 4_Machine learning-based integration of DCE-MRI radiomics for STAT3 expression prediction and survival stratification in breast cancer.tif by Dong Pan (1835707)

“…A STAT3 predictive model was developed using six machine learning algorithms. Model performance was assessed using receiver operating characteristic (ROC) and related diagnostic statistical indicators.…”

Data Sheet 1_Tumor tissue-of-origin classification using miRNA-mRNA-lncRNA interaction networks and machine learning methods.docx by Ankita Lawarde (16544943)

“…In addition, functional enrichment analyses indicated significant involvement of miRNAs in pathways such as TGF-beta signaling, epithelial-mesenchymal transition, and immune modulation. …”

Table 7_Machine learning-based integration of DCE-MRI radiomics for STAT3 expression prediction and survival stratification in breast cancer.docx by Dong Pan (1835707)

“…A STAT3 predictive model was developed using six machine learning algorithms. Model performance was assessed using receiver operating characteristic (ROC) and related diagnostic statistical indicators.…”

Table 5_Machine learning-based integration of DCE-MRI radiomics for STAT3 expression prediction and survival stratification in breast cancer.docx by Dong Pan (1835707)

“…A STAT3 predictive model was developed using six machine learning algorithms. Model performance was assessed using receiver operating characteristic (ROC) and related diagnostic statistical indicators.…”

Image 9_Machine learning-based integration of DCE-MRI radiomics for STAT3 expression prediction and survival stratification in breast cancer.tif by Dong Pan (1835707)

“…A STAT3 predictive model was developed using six machine learning algorithms. Model performance was assessed using receiver operating characteristic (ROC) and related diagnostic statistical indicators.…”

Table 6_Machine learning-based integration of DCE-MRI radiomics for STAT3 expression prediction and survival stratification in breast cancer.xlsx by Dong Pan (1835707)

“…A STAT3 predictive model was developed using six machine learning algorithms. Model performance was assessed using receiver operating characteristic (ROC) and related diagnostic statistical indicators.…”

Image 1_Machine learning-based integration of DCE-MRI radiomics for STAT3 expression prediction and survival stratification in breast cancer.tif by Dong Pan (1835707)

“…A STAT3 predictive model was developed using six machine learning algorithms. Model performance was assessed using receiver operating characteristic (ROC) and related diagnostic statistical indicators.…”

Image3_Fatty acid metabolism prognostic signature predicts tumor immune microenvironment and immunotherapy, and identifies tumorigenic role of MOGAT2 in lung adenocarcinoma.tif by Denggang Fu (5082062)

“…Tumor immune microenvironment (TIME) was analyzed using ESTIMATE and multiple deconvolution algorithms. Functional assays, including CCK8, cell cycle, apoptosis, transwell, and wound healing assays, were performed on MOGAT2-silenced H1299 cells using CRISPR/Cas9 technology.…”

Image4_Fatty acid metabolism prognostic signature predicts tumor immune microenvironment and immunotherapy, and identifies tumorigenic role of MOGAT2 in lung adenocarcinoma.tif by Denggang Fu (5082062)

“…Tumor immune microenvironment (TIME) was analyzed using ESTIMATE and multiple deconvolution algorithms. Functional assays, including CCK8, cell cycle, apoptosis, transwell, and wound healing assays, were performed on MOGAT2-silenced H1299 cells using CRISPR/Cas9 technology.…”

Image2_Fatty acid metabolism prognostic signature predicts tumor immune microenvironment and immunotherapy, and identifies tumorigenic role of MOGAT2 in lung adenocarcinoma.tif by Denggang Fu (5082062)

“…Tumor immune microenvironment (TIME) was analyzed using ESTIMATE and multiple deconvolution algorithms. Functional assays, including CCK8, cell cycle, apoptosis, transwell, and wound healing assays, were performed on MOGAT2-silenced H1299 cells using CRISPR/Cas9 technology.…”

Image5_Fatty acid metabolism prognostic signature predicts tumor immune microenvironment and immunotherapy, and identifies tumorigenic role of MOGAT2 in lung adenocarcinoma.tif by Denggang Fu (5082062)

“…Tumor immune microenvironment (TIME) was analyzed using ESTIMATE and multiple deconvolution algorithms. Functional assays, including CCK8, cell cycle, apoptosis, transwell, and wound healing assays, were performed on MOGAT2-silenced H1299 cells using CRISPR/Cas9 technology.…”

DataSheet1_Fatty acid metabolism prognostic signature predicts tumor immune microenvironment and immunotherapy, and identifies tumorigenic role of MOGAT2 in lung adenocarcinoma.pdf by Denggang Fu (5082062)

“…Tumor immune microenvironment (TIME) was analyzed using ESTIMATE and multiple deconvolution algorithms. Functional assays, including CCK8, cell cycle, apoptosis, transwell, and wound healing assays, were performed on MOGAT2-silenced H1299 cells using CRISPR/Cas9 technology.…”

Image1_Fatty acid metabolism prognostic signature predicts tumor immune microenvironment and immunotherapy, and identifies tumorigenic role of MOGAT2 in lung adenocarcinoma.tif by Denggang Fu (5082062)

“…Tumor immune microenvironment (TIME) was analyzed using ESTIMATE and multiple deconvolution algorithms. Functional assays, including CCK8, cell cycle, apoptosis, transwell, and wound healing assays, were performed on MOGAT2-silenced H1299 cells using CRISPR/Cas9 technology.…”