Data Sheet 3_The role and machine learning analysis of mitochondrial autophagy-related gene expression in lung adenocarcinoma.pdf حسب Binyu Wang (7375019)

"…Machine learning algorithms identified COASY, FTSJ1, and MOGS as pivotal genes. …"

Data Sheet 1_Identification and validation of the nicotine metabolism-related signature of bladder cancer by bioinformatics and machine learning.zip حسب Yating Zhan (5048351)

"…Prognostic differentially expressed genes (DEGs) were filtered via differentially expression analysis and univariate Cox regression analysis. Integrative machine learning combination based on 10 machine learning algorithms was used for the construction of robust signature. …"

A Machine-Insight-Based Geocomputational Approach to Decode the Complexities of the Restless Landscapes: Toward Integration of Imaginations and Planning Interventions حسب Nilanjan Bal (21727652)

"…The learning cloud incorporates settlement-wise data in an encoded format to run the XGBoost machine learning algorithm. The findings highlight a competitive pattern of settlements and identify four periurban zones based on the deviation diffusion of calculated parameters. …"

Data Sheet 2_Machine learning-driven discovery of NETs-associated diagnostic biomarkers and molecular subtypes in tuberculosis.pdf حسب Shoupeng Ding (21555394)

"…Differential analysis, WGCNA, and an ensemble of 113 machine learning algorithms were employed to identify the core NETs genes. …"

Data Sheet 1_Machine learning-driven discovery of NETs-associated diagnostic biomarkers and molecular subtypes in tuberculosis.pdf حسب Shoupeng Ding (21555394)

"…Differential analysis, WGCNA, and an ensemble of 113 machine learning algorithms were employed to identify the core NETs genes. …"

Network toxicology and machine learning reveal key molecular targets and pathways of mono-2-ethylhexyl phthalate-induced atherosclerosis حسب Qiu Sun (1607974)

"…Machine learning algorithms including LASSO regression, RF, and SVM were employed to identify key targets. …"

Image 1_Identification of neutrophil extracellular trap-related biomarkers in ulcerative colitis based on bioinformatics and machine learning.tif حسب Jiao Li (261359)

"…Differentially expressed genes (DEGs) related to NETs in UC patients and healthy controls were identified using Limma R package and WGCNA, followed by functional enrichment analysis. To identify potential diagnostic biomarkers, we applied the Least Absolute Shrinkage and Selection Operator (LASSO), Support Vector Machine-Recursive Feature Elimination (SVM-RFE) model, and Random Forest (RF) algorithm, and constructed Receiver Operating Characteristic (ROC) curves to evaluate accuracy. …"

Table 1_Identification of neutrophil extracellular trap-related biomarkers in ulcerative colitis based on bioinformatics and machine learning.docx حسب Jiao Li (261359)

"…Differentially expressed genes (DEGs) related to NETs in UC patients and healthy controls were identified using Limma R package and WGCNA, followed by functional enrichment analysis. To identify potential diagnostic biomarkers, we applied the Least Absolute Shrinkage and Selection Operator (LASSO), Support Vector Machine-Recursive Feature Elimination (SVM-RFE) model, and Random Forest (RF) algorithm, and constructed Receiver Operating Characteristic (ROC) curves to evaluate accuracy. …"

Image 2_Identification of neutrophil extracellular trap-related biomarkers in ulcerative colitis based on bioinformatics and machine learning.tif حسب Jiao Li (261359)

"…Differentially expressed genes (DEGs) related to NETs in UC patients and healthy controls were identified using Limma R package and WGCNA, followed by functional enrichment analysis. To identify potential diagnostic biomarkers, we applied the Least Absolute Shrinkage and Selection Operator (LASSO), Support Vector Machine-Recursive Feature Elimination (SVM-RFE) model, and Random Forest (RF) algorithm, and constructed Receiver Operating Characteristic (ROC) curves to evaluate accuracy. …"

Image 1_Integrative analysis of PANoptosis-related genes in diabetic retinopathy: machine learning identification and experimental validation.tif حسب Han Chen (228557)

"…Three machine learning algorithms—LASSO regression, Random Forest, and SVM-RFE—were employed to identify hub genes. …"

Table 1_Integrative analysis of PANoptosis-related genes in diabetic retinopathy: machine learning identification and experimental validation.docx حسب Han Chen (228557)

"…Three machine learning algorithms—LASSO regression, Random Forest, and SVM-RFE—were employed to identify hub genes. …"

Table 2_Integrative analysis of PANoptosis-related genes in diabetic retinopathy: machine learning identification and experimental validation.xlsx حسب Han Chen (228557)

"…Three machine learning algorithms—LASSO regression, Random Forest, and SVM-RFE—were employed to identify hub genes. …"

Image 5_Identification of ferroptosis-genes associated with pediatric inflammatory bowel disease bioinformatics and machine learning approaches.tif حسب Zhen Xu (92379)

"…</p>Methods<p>RNA-seq data of PIBD from GEO datasets were analyzed using DESeq2, WGCNA, and functional enrichment analysis. Ferroptosis-related diagnostic genes were screened through LASSO, Random Forest, and mSVM-RFE algorithms, and validated in GSE57945 and GSE117993 datasets. …"

Image 1_Identification of ferroptosis-genes associated with pediatric inflammatory bowel disease bioinformatics and machine learning approaches.tif حسب Zhen Xu (92379)

"…</p>Methods<p>RNA-seq data of PIBD from GEO datasets were analyzed using DESeq2, WGCNA, and functional enrichment analysis. Ferroptosis-related diagnostic genes were screened through LASSO, Random Forest, and mSVM-RFE algorithms, and validated in GSE57945 and GSE117993 datasets. …"

Image 2_Identification of ferroptosis-genes associated with pediatric inflammatory bowel disease bioinformatics and machine learning approaches.tif حسب Zhen Xu (92379)

"…</p>Methods<p>RNA-seq data of PIBD from GEO datasets were analyzed using DESeq2, WGCNA, and functional enrichment analysis. Ferroptosis-related diagnostic genes were screened through LASSO, Random Forest, and mSVM-RFE algorithms, and validated in GSE57945 and GSE117993 datasets. …"

Table 5_Identification of ferroptosis-genes associated with pediatric inflammatory bowel disease bioinformatics and machine learning approaches.xlsx حسب Zhen Xu (92379)

"…</p>Methods<p>RNA-seq data of PIBD from GEO datasets were analyzed using DESeq2, WGCNA, and functional enrichment analysis. Ferroptosis-related diagnostic genes were screened through LASSO, Random Forest, and mSVM-RFE algorithms, and validated in GSE57945 and GSE117993 datasets. …"

Table 7_Identification of ferroptosis-genes associated with pediatric inflammatory bowel disease bioinformatics and machine learning approaches.xlsx حسب Zhen Xu (92379)

"…</p>Methods<p>RNA-seq data of PIBD from GEO datasets were analyzed using DESeq2, WGCNA, and functional enrichment analysis. Ferroptosis-related diagnostic genes were screened through LASSO, Random Forest, and mSVM-RFE algorithms, and validated in GSE57945 and GSE117993 datasets. …"

Table 2_Identification of ferroptosis-genes associated with pediatric inflammatory bowel disease bioinformatics and machine learning approaches.docx حسب Zhen Xu (92379)

"…</p>Methods<p>RNA-seq data of PIBD from GEO datasets were analyzed using DESeq2, WGCNA, and functional enrichment analysis. Ferroptosis-related diagnostic genes were screened through LASSO, Random Forest, and mSVM-RFE algorithms, and validated in GSE57945 and GSE117993 datasets. …"

Table 4_Identification of ferroptosis-genes associated with pediatric inflammatory bowel disease bioinformatics and machine learning approaches.xlsx حسب Zhen Xu (92379)

"…</p>Methods<p>RNA-seq data of PIBD from GEO datasets were analyzed using DESeq2, WGCNA, and functional enrichment analysis. Ferroptosis-related diagnostic genes were screened through LASSO, Random Forest, and mSVM-RFE algorithms, and validated in GSE57945 and GSE117993 datasets. …"

Table 1_Identification of ferroptosis-genes associated with pediatric inflammatory bowel disease bioinformatics and machine learning approaches.xlsx حسب Zhen Xu (92379)

"…</p>Methods<p>RNA-seq data of PIBD from GEO datasets were analyzed using DESeq2, WGCNA, and functional enrichment analysis. Ferroptosis-related diagnostic genes were screened through LASSO, Random Forest, and mSVM-RFE algorithms, and validated in GSE57945 and GSE117993 datasets. …"