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)

“…</p>Methods<p>Data from 1,008 patients with breast cancer in The Cancer Genome Atlas were analyzed to evaluate the prognostic significance of STAT3 expression using Kaplan-Meier survival analysis and Cox regression models. Functional enrichment and immune cell infiltration analyses were performed to assess tumor immune microenvironment characteristics. …”

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)

“…</p>Methods<p>Data from 1,008 patients with breast cancer in The Cancer Genome Atlas were analyzed to evaluate the prognostic significance of STAT3 expression using Kaplan-Meier survival analysis and Cox regression models. Functional enrichment and immune cell infiltration analyses were performed to assess tumor immune microenvironment characteristics. …”

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)

“…</p>Methods<p>Data from 1,008 patients with breast cancer in The Cancer Genome Atlas were analyzed to evaluate the prognostic significance of STAT3 expression using Kaplan-Meier survival analysis and Cox regression models. Functional enrichment and immune cell infiltration analyses were performed to assess tumor immune microenvironment characteristics. …”

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)

“…Weighted gene co-expression network analysis (WGCNA) was employed to delineate modules significantly associated with UC and CRC, and the intersection of DEGs, key module genes, and senescence‐related genes from the CellAge database yielded 112 candidate genes. An integrated machine learning (IML) model—utilizing 12 algorithms with 10-fold cross-validation—was constructed to pinpoint key diagnostic biomarkers. …”

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)

“…</p>Methods<p>Data from 1,008 patients with breast cancer in The Cancer Genome Atlas were analyzed to evaluate the prognostic significance of STAT3 expression using Kaplan-Meier survival analysis and Cox regression models. Functional enrichment and immune cell infiltration analyses were performed to assess tumor immune microenvironment characteristics. …”

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)

“…</p>Methods<p>Data from 1,008 patients with breast cancer in The Cancer Genome Atlas were analyzed to evaluate the prognostic significance of STAT3 expression using Kaplan-Meier survival analysis and Cox regression models. Functional enrichment and immune cell infiltration analyses were performed to assess tumor immune microenvironment characteristics. …”

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)

“…</p>Methods<p>Data from 1,008 patients with breast cancer in The Cancer Genome Atlas were analyzed to evaluate the prognostic significance of STAT3 expression using Kaplan-Meier survival analysis and Cox regression models. Functional enrichment and immune cell infiltration analyses were performed to assess tumor immune microenvironment characteristics. …”

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)

“…</p>Methods<p>Data from 1,008 patients with breast cancer in The Cancer Genome Atlas were analyzed to evaluate the prognostic significance of STAT3 expression using Kaplan-Meier survival analysis and Cox regression models. Functional enrichment and immune cell infiltration analyses were performed to assess tumor immune microenvironment characteristics. …”

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)

“…Weighted gene co-expression network analysis (WGCNA) was employed to delineate modules significantly associated with UC and CRC, and the intersection of DEGs, key module genes, and senescence‐related genes from the CellAge database yielded 112 candidate genes. An integrated machine learning (IML) model—utilizing 12 algorithms with 10-fold cross-validation—was constructed to pinpoint key diagnostic biomarkers. …”

Data Sheet 2_Integration of multi-omics and machine learning strategies identifies immune related candidate biomarkers in inflammation-associated hypertrophic cardiomyopathy.csv by Qingzhu Liang (22315633)

“…Functional enrichment was performed with clusterProfiler, diagnostic performance was evaluated via ROC curves, and immune cell infiltration was analyzed using CIBERSORT. …”

Table 1_Identification and verification of biomarkers associated with neutrophils in acute myocardial infarction: integrated analysis of bulk RNA-seq, expression quantitative trait... by Guoqing Liu (93712)

“…Hub genes were screened using the least absolute shrinkage and selection operator (LASSO) and random forest (RF) algorithms. A cellular model of AMI was established using oxygen- and glucose-deprived AC16 cells. …”

Data Sheet 5_Integration of multi-omics and machine learning strategies identifies immune related candidate biomarkers in inflammation-associated hypertrophic cardiomyopathy.csv by Qingzhu Liang (22315633)

“…Functional enrichment was performed with clusterProfiler, diagnostic performance was evaluated via ROC curves, and immune cell infiltration was analyzed using CIBERSORT. …”

Data Sheet 1_Identification and verification of biomarkers associated with neutrophils in acute myocardial infarction: integrated analysis of bulk RNA-seq, expression quantitative... by Guoqing Liu (93712)

“…Hub genes were screened using the least absolute shrinkage and selection operator (LASSO) and random forest (RF) algorithms. A cellular model of AMI was established using oxygen- and glucose-deprived AC16 cells. …”

Table 1_Prognostic and immunological implications of cathepsin Z overexpression in prostate cancer.docx by Junyue Tao (13817719)

“…Immunohistochemical staining and multiplex immunofluorescence staining were performed to evaluate the expression and spatial distribution of CTSZ and immune-related markers in PCa tissues. Functional studies were conducted through a series of experiments, including CCK-8 assay, colony formation, wound healing, and Transwell migration assays. ssGSEA and CIBERSORT algorithms immune infiltration evaluation, and GISTIC2.0 and MutSigCV for tumor mutation burden. …”

Data Sheet 4_Integration of multi-omics and machine learning strategies identifies immune related candidate biomarkers in inflammation-associated hypertrophic cardiomyopathy.csv by Qingzhu Liang (22315633)

“…Functional enrichment was performed with clusterProfiler, diagnostic performance was evaluated via ROC curves, and immune cell infiltration was analyzed using CIBERSORT. …”

Table 2_Identification and verification of biomarkers associated with neutrophils in acute myocardial infarction: integrated analysis of bulk RNA-seq, expression quantitative trait... by Guoqing Liu (93712)

“…Hub genes were screened using the least absolute shrinkage and selection operator (LASSO) and random forest (RF) algorithms. A cellular model of AMI was established using oxygen- and glucose-deprived AC16 cells. …”

Data Sheet 1_Integration of multi-omics and machine learning strategies identifies immune related candidate biomarkers in inflammation-associated hypertrophic cardiomyopathy.csv by Qingzhu Liang (22315633)

“…Functional enrichment was performed with clusterProfiler, diagnostic performance was evaluated via ROC curves, and immune cell infiltration was analyzed using CIBERSORT. …”

Data Sheet 3_Integration of multi-omics and machine learning strategies identifies immune related candidate biomarkers in inflammation-associated hypertrophic cardiomyopathy.csv by Qingzhu Liang (22315633)

“…Functional enrichment was performed with clusterProfiler, diagnostic performance was evaluated via ROC curves, and immune cell infiltration was analyzed using CIBERSORT. …”

Data Sheet 1_Identification of key ferroptosis-related genes and therapeutic target in nasopharyngeal carcinoma.zip by Yuanyuan Gu (3813658)

“…Functional enrichment (GSEA, GSVA), drug prediction (DGIdb), immune infiltration analysis (CIBERSORT), and single-cell RNA sequencing (scRNA-seq) were performed.…”

Turkish_native_goat_genotypes by Yalçın YAMAN (20209833)

“…An ensemble feature-importance analysis, evaluated through 10,000 permutations, identified 31 FDR-significant SNPs representing markers consistently associated with MAP status. Functional annotation indicated involvement of immune-related processes such as cytokine–receptor signalling, antigen presentation, glycan-mediated T-cell regulation, and NF-κB–linked inflammatory pathways. …”