Image 2_Machine learning-driven exploration of therapeutic targets for atrial fibrillation-joint analysis of single-cell and bulk transcriptomes and experimental validation.tif حسب Yicheng Wang (810922)

"…Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Disease Ontology (DO) enrichment analyses were conducted to explore the functions and pathways of these DEGs. Three machine learning algorithms, Least Absolute Shrinkage and Selection Operator (LASSO), Support Vector Machine—Recursive Feature Elimination (SVM-RFE), and random forest (RF), were applied to screen key genes related to AF. …"

Image 4_Identification of genes associated with disulfidptosis in the subacute phase of spinal cord injury and analysis of potential therapeutic targets.jpeg حسب Shenglong Wang (569676)

"…Key diagnostic genes were screened by random forest and LASSO algorithms and validated via receiver operating characteristic (ROC) analysis. …"

Image2_Identification of novel biomarkers, shared molecular signatures and immune cell infiltration in heart and kidney failure by transcriptomics.tif حسب Qingqing Long (845156)

"…A protein-protein interaction (PPI) network was constructed, and machine learning algorithms, including Random Forest (RF), Support Vector Machine-Recursive Feature Elimination (SVM-RFE), and Least Absolute Shrinkage and Selection Operator (LASSO), were used to identify key signature genes. …"

Data Sheet 3_Key gene screening and diagnostic model establishment for acute type a aortic dissection.csv حسب Yue Pan (267516)

"…</p>Methods<p>Transcriptome datasets from the Gene Expression Omnibus (GEO) database were analyzed using differential expression analysis, weighted gene co-expression network analysis (WGCNA), and machine learning algorithms (SVM, Random Forest, LASSO regression). …"

Image1_Identification of novel biomarkers, shared molecular signatures and immune cell infiltration in heart and kidney failure by transcriptomics.tif حسب Qingqing Long (845156)

"…A protein-protein interaction (PPI) network was constructed, and machine learning algorithms, including Random Forest (RF), Support Vector Machine-Recursive Feature Elimination (SVM-RFE), and Least Absolute Shrinkage and Selection Operator (LASSO), were used to identify key signature genes. …"

Data Sheet 1_CDK1 may promote breast cancer progression through AKT activation and immune modulation.docx حسب Huanhong Zeng (22570433)

"…Immune infiltration and tumor mutation burden (TMB) were evaluated using TIMER and CIBERSORT algorithms. Single-cell RNA sequencing data from TISCH2 were employed to examine cell-type-specific expression. …"

Data Sheet 2_Key gene screening and diagnostic model establishment for acute type a aortic dissection.csv حسب Yue Pan (267516)

"…</p>Methods<p>Transcriptome datasets from the Gene Expression Omnibus (GEO) database were analyzed using differential expression analysis, weighted gene co-expression network analysis (WGCNA), and machine learning algorithms (SVM, Random Forest, LASSO regression). …"

Image 3_UBE2N as a novel prognostic and therapeutic biomarker of lung adenocarcinoma.tif حسب Haofeng Yin (19931343)

"…The role of UBE2N in predicting tumor therapeutic susceptibility was characterized using bioinformatics algorithms combined with publicly available CRISPR screening datasets and immunotherapy cohorts. …"

Image 5_UBE2N as a novel prognostic and therapeutic biomarker of lung adenocarcinoma.tif حسب Haofeng Yin (19931343)

"…The role of UBE2N in predicting tumor therapeutic susceptibility was characterized using bioinformatics algorithms combined with publicly available CRISPR screening datasets and immunotherapy cohorts. …"

Table 1_Key gene screening and diagnostic model establishment for acute type a aortic dissection.xlsx حسب Yue Pan (267516)

"…</p>Methods<p>Transcriptome datasets from the Gene Expression Omnibus (GEO) database were analyzed using differential expression analysis, weighted gene co-expression network analysis (WGCNA), and machine learning algorithms (SVM, Random Forest, LASSO regression). …"

Image 1_UBE2N as a novel prognostic and therapeutic biomarker of lung adenocarcinoma.tif حسب Haofeng Yin (19931343)

"…The role of UBE2N in predicting tumor therapeutic susceptibility was characterized using bioinformatics algorithms combined with publicly available CRISPR screening datasets and immunotherapy cohorts. …"

Image 4_UBE2N as a novel prognostic and therapeutic biomarker of lung adenocarcinoma.tif حسب Haofeng Yin (19931343)

"…The role of UBE2N in predicting tumor therapeutic susceptibility was characterized using bioinformatics algorithms combined with publicly available CRISPR screening datasets and immunotherapy cohorts. …"

Data Sheet 4_Key gene screening and diagnostic model establishment for acute type a aortic dissection.csv حسب Yue Pan (267516)

"…</p>Methods<p>Transcriptome datasets from the Gene Expression Omnibus (GEO) database were analyzed using differential expression analysis, weighted gene co-expression network analysis (WGCNA), and machine learning algorithms (SVM, Random Forest, LASSO regression). …"

DataSheet1_Identification of novel biomarkers, shared molecular signatures and immune cell infiltration in heart and kidney failure by transcriptomics.docx حسب Qingqing Long (845156)

"…A protein-protein interaction (PPI) network was constructed, and machine learning algorithms, including Random Forest (RF), Support Vector Machine-Recursive Feature Elimination (SVM-RFE), and Least Absolute Shrinkage and Selection Operator (LASSO), were used to identify key signature genes. …"

Table 1_UBE2N as a novel prognostic and therapeutic biomarker of lung adenocarcinoma.docx حسب Haofeng Yin (19931343)

"…The role of UBE2N in predicting tumor therapeutic susceptibility was characterized using bioinformatics algorithms combined with publicly available CRISPR screening datasets and immunotherapy cohorts. …"

Data Sheet 5_Key gene screening and diagnostic model establishment for acute type a aortic dissection.csv حسب Yue Pan (267516)

"…</p>Methods<p>Transcriptome datasets from the Gene Expression Omnibus (GEO) database were analyzed using differential expression analysis, weighted gene co-expression network analysis (WGCNA), and machine learning algorithms (SVM, Random Forest, LASSO regression). …"

Data Sheet 1_Key gene screening and diagnostic model establishment for acute type a aortic dissection.csv حسب Yue Pan (267516)

"…</p>Methods<p>Transcriptome datasets from the Gene Expression Omnibus (GEO) database were analyzed using differential expression analysis, weighted gene co-expression network analysis (WGCNA), and machine learning algorithms (SVM, Random Forest, LASSO regression). …"

Image 2_UBE2N as a novel prognostic and therapeutic biomarker of lung adenocarcinoma.tif حسب Haofeng Yin (19931343)

"…The role of UBE2N in predicting tumor therapeutic susceptibility was characterized using bioinformatics algorithms combined with publicly available CRISPR screening datasets and immunotherapy cohorts. …"

Image 5_Single-cell and machine learning-based pyroptosis-related gene signature predicts prognosis and immunotherapy response in glioblastoma.tif حسب Liren Fang (22489516)

"…Candidate prognostic genes identified from malignant epithelial subsets were further used to develop a Pyroptosis-Related Gene Signature (PRGS) through a systematic evaluation of ten machine learning algorithms and their combinations, with subsequent validation across multiple cohorts. …"

Image 3_Single-cell and machine learning-based pyroptosis-related gene signature predicts prognosis and immunotherapy response in glioblastoma.tif حسب Liren Fang (22489516)

"…Candidate prognostic genes identified from malignant epithelial subsets were further used to develop a Pyroptosis-Related Gene Signature (PRGS) through a systematic evaluation of ten machine learning algorithms and their combinations, with subsequent validation across multiple cohorts. …"