Breast cancer specific subnetwork. by Bengi Ruken Yavuz (21983004)

Psoas muscle CT radiomics-based machine learning models to predict response to infliximab in patients with Crohn’s disease by Zhuoyan Chen (12193358)

“…<i>Z</i> score standardization and independent sample <i>t</i> test were applied to identify optimal predictive features, which were then utilized in seven ML algorithms for training and validation. …”

DataSheet_1_Expression patterns and immunological characterization of PANoptosis -related genes in gastric cancer.zip by Xin Qing (10730751)

“…The differentially expressed genes were determined with the WGCNA method. Afterward, we employed four machine learning algorithms (Random Forest, Support Vector Machine, Generalized linear Model, and eXtreme Gradient Boosting) to select the optimal model, which was validated using nomogram, calibration curve, decision curve analysis (DCA), and two validation cohorts. …”

CD4 T cell subset composition in 17ZR101-infection. by Qi Xu (134661)

Table_2_Construction of a prognostic model of colon cancer patients based on metabolism-related lncRNAs.xls by Chenyang Li (532326)

“…Enrichment analysis of KEGG pathway revealed that differential lncRNAs may be related to chemokines, amino acid and sugar metabolism, NOD-like receptor and Toll-like receptor activation as well as other pathways. Finally, the analysis results based on the CIBERSORT algorithm showed that the lncRNAs used to construct the model had a strong polarized correlation with B cells, CD8+T cells and M0 macrophages.…”

Table_1_Construction of a prognostic model of colon cancer patients based on metabolism-related lncRNAs.xls by Chenyang Li (532326)

“…Enrichment analysis of KEGG pathway revealed that differential lncRNAs may be related to chemokines, amino acid and sugar metabolism, NOD-like receptor and Toll-like receptor activation as well as other pathways. Finally, the analysis results based on the CIBERSORT algorithm showed that the lncRNAs used to construct the model had a strong polarized correlation with B cells, CD8+T cells and M0 macrophages.…”

Table_4_Construction of a prognostic model of colon cancer patients based on metabolism-related lncRNAs.xlsx by Chenyang Li (532326)

“…Enrichment analysis of KEGG pathway revealed that differential lncRNAs may be related to chemokines, amino acid and sugar metabolism, NOD-like receptor and Toll-like receptor activation as well as other pathways. Finally, the analysis results based on the CIBERSORT algorithm showed that the lncRNAs used to construct the model had a strong polarized correlation with B cells, CD8+T cells and M0 macrophages.…”

Table_5_Construction of a prognostic model of colon cancer patients based on metabolism-related lncRNAs.xlsx by Chenyang Li (532326)

“…Enrichment analysis of KEGG pathway revealed that differential lncRNAs may be related to chemokines, amino acid and sugar metabolism, NOD-like receptor and Toll-like receptor activation as well as other pathways. Finally, the analysis results based on the CIBERSORT algorithm showed that the lncRNAs used to construct the model had a strong polarized correlation with B cells, CD8+T cells and M0 macrophages.…”

Table_3_Construction of a prognostic model of colon cancer patients based on metabolism-related lncRNAs.xlsx by Chenyang Li (532326)

“…Enrichment analysis of KEGG pathway revealed that differential lncRNAs may be related to chemokines, amino acid and sugar metabolism, NOD-like receptor and Toll-like receptor activation as well as other pathways. Finally, the analysis results based on the CIBERSORT algorithm showed that the lncRNAs used to construct the model had a strong polarized correlation with B cells, CD8+T cells and M0 macrophages.…”

Table_3_Vesicle-mediated transport-related genes are prognostic predictors and are associated with tumor immunity in lung adenocarcinoma.xlsx by Changrui Qian (8041325)

“…The roles of these genes were investigated via the Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene ontology (GO) enrichment analyses. …”

Table_1_Vesicle-mediated transport-related genes are prognostic predictors and are associated with tumor immunity in lung adenocarcinoma.xlsx by Changrui Qian (8041325)

“…The roles of these genes were investigated via the Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene ontology (GO) enrichment analyses. …”

Table_2_Vesicle-mediated transport-related genes are prognostic predictors and are associated with tumor immunity in lung adenocarcinoma.xlsx by Changrui Qian (8041325)

“…The roles of these genes were investigated via the Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene ontology (GO) enrichment analyses. …”

Table_4_Vesicle-mediated transport-related genes are prognostic predictors and are associated with tumor immunity in lung adenocarcinoma.xlsx by Changrui Qian (8041325)

“…The roles of these genes were investigated via the Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene ontology (GO) enrichment analyses. …”

Image_1_Vesicle-mediated transport-related genes are prognostic predictors and are associated with tumor immunity in lung adenocarcinoma.tif by Changrui Qian (8041325)

“…The roles of these genes were investigated via the Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene ontology (GO) enrichment analyses. …”

DataSheet_1_Identification of colon cancer subtypes based on multi-omics data—construction of methylation markers for immunotherapy.zip by Benjie Xu (13813594)

Table 1_A novel, rapid, and practical prognostic model for sepsis patients based on dysregulated immune cell lactylation.xlsx by Chang Li (133800)

“…Patients were stratified into subgroups using k-means clustering based on lactylation levels. Machine learning algorithms, integrated with pseudotime trajectory reconstruction, were employed to map the temporal dynamics of lactylation. …”

Table 3_A novel, rapid, and practical prognostic model for sepsis patients based on dysregulated immune cell lactylation.docx by Chang Li (133800)

“…Patients were stratified into subgroups using k-means clustering based on lactylation levels. Machine learning algorithms, integrated with pseudotime trajectory reconstruction, were employed to map the temporal dynamics of lactylation. …”

Table 4_A novel, rapid, and practical prognostic model for sepsis patients based on dysregulated immune cell lactylation.xlsx by Chang Li (133800)

“…Patients were stratified into subgroups using k-means clustering based on lactylation levels. Machine learning algorithms, integrated with pseudotime trajectory reconstruction, were employed to map the temporal dynamics of lactylation. …”

Table 2_A novel, rapid, and practical prognostic model for sepsis patients based on dysregulated immune cell lactylation.docx by Chang Li (133800)

“…Patients were stratified into subgroups using k-means clustering based on lactylation levels. Machine learning algorithms, integrated with pseudotime trajectory reconstruction, were employed to map the temporal dynamics of lactylation. …”

Table_4_Computed Tomography Imaging-Based Radiogenomics Analysis Reveals Hypoxia Patterns and Immunological Characteristics in Ovarian Cancer.xlsx by Songwei Feng (11200268)

“…Finally, optimal radiogenomics biomarkers for predicting the risk status of patients were developed by machine learning algorithms.…”