Search alternatives:
algorithm python » algorithm within (Expand Search), algorithms within (Expand Search)
python function » protein function (Expand Search)
algorithm both » algorithm blood (Expand Search), algorithm b (Expand Search), algorithm etc (Expand Search)
algorithm python » algorithm within (Expand Search), algorithms within (Expand Search)
python function » protein function (Expand Search)
algorithm both » algorithm blood (Expand Search), algorithm b (Expand Search), algorithm etc (Expand Search)
-
881
Data Sheet 1_Novel diagnostic biomarkers associated with macrophage-microglia in spinal cord injury.pdf
Published 2025“…Predictive models based on these genes demonstrated strong performance in both internal training and external validation cohorts. …”
-
882
Table 4_Novel diagnostic biomarkers associated with macrophage-microglia in spinal cord injury.xlsx
Published 2025“…Predictive models based on these genes demonstrated strong performance in both internal training and external validation cohorts. …”
-
883
Table 1_Novel diagnostic biomarkers associated with macrophage-microglia in spinal cord injury.xlsx
Published 2025“…Predictive models based on these genes demonstrated strong performance in both internal training and external validation cohorts. …”
-
884
Image 1_Immune-molecular nexus in reproductive disorders: mechanisms linking POI and RSA.pdf
Published 2025“…The analysis involved machine learning algorithms, mcode and Cytoscape, revealing important hub genes. …”
-
885
Data Sheet 2_Novel diagnostic biomarkers associated with macrophage-microglia in spinal cord injury.pdf
Published 2025“…Predictive models based on these genes demonstrated strong performance in both internal training and external validation cohorts. …”
-
886
Supplementary file 1_Novel diagnostic biomarkers associated with macrophage-microglia in spinal cord injury.xlsx
Published 2025“…Predictive models based on these genes demonstrated strong performance in both internal training and external validation cohorts. …”
-
887
Table 2_Novel diagnostic biomarkers associated with macrophage-microglia in spinal cord injury.xlsx
Published 2025“…Predictive models based on these genes demonstrated strong performance in both internal training and external validation cohorts. …”
-
888
Supplementary file 2_Novel diagnostic biomarkers associated with macrophage-microglia in spinal cord injury.xlsx
Published 2025“…Predictive models based on these genes demonstrated strong performance in both internal training and external validation cohorts. …”
-
889
Table 3_Novel diagnostic biomarkers associated with macrophage-microglia in spinal cord injury.xlsx
Published 2025“…Predictive models based on these genes demonstrated strong performance in both internal training and external validation cohorts. …”
-
890
Table 2_Construction and validation of immune prognosis model for lung adenocarcinoma based on machine learning.docx
Published 2025“…Three machine learning algorithms—Random Forest, LASSO, and SVM-RFE—were applied to identify key hub genes. …”
-
891
Supplementary file 1_Probiotic modulation of maternal gut and milk microbiota and potential implications for infant microbial development in the perinatal period.docx
Published 2025“…However, LEfSe revealed distinct genera in both maternal gut and milk microbiota linked to probiotic intake. …”
-
892
Table 1_Construction and validation of immune prognosis model for lung adenocarcinoma based on machine learning.docx
Published 2025“…Three machine learning algorithms—Random Forest, LASSO, and SVM-RFE—were applied to identify key hub genes. …”
-
893
Table 2_Comprehensive analysis of immunogenic cell death-related genes in liver ischemia-reperfusion injury.xlsx
Published 2025“…The RF and SVM machine learning algorithms were finally chosen to construct the models. …”
-
894
Supplementary file 1_Transcriptomic analysis and machine learning modeling identifies novel biomarkers and genetic characteristics of hypertrophic cardiomyopathy.xlsx
Published 2025“…A predictive model for HCM was developed through systematic evaluation of 113 combinations of 12 machine-learning algorithms, employing 10-fold cross-validation on training datasets and external validation using an independent cohort (GSE180313).…”
-
895
Supplementary file 1_Plasma FGF2 and YAP1 as novel biomarkers for MCI in the elderly: analysis via bioinformatics and clinical study.docx
Published 2025“…However, there is still a notable absence of novel biomarkers that are both efficient, minimally invasive, and cost-effective in real-world clinical settings. …”
-
896
Table 1_Comprehensive analysis of immunogenic cell death-related genes in liver ischemia-reperfusion injury.xlsx
Published 2025“…The RF and SVM machine learning algorithms were finally chosen to construct the models. …”
-
897
Image1_Exploring the pathogenesis, biomarkers, and potential drugs for type 2 diabetes mellitus and acute pancreatitis through a comprehensive bioinformatic analysis.pdf
Published 2024“…Subsequently, we used several machine learning algorithms to identify candidate biomarkers and construct a diagnostic nomogram for T2DM and AP. …”
-
898
Table1_Exploring the pathogenesis, biomarkers, and potential drugs for type 2 diabetes mellitus and acute pancreatitis through a comprehensive bioinformatic analysis.xlsx
Published 2024“…Subsequently, we used several machine learning algorithms to identify candidate biomarkers and construct a diagnostic nomogram for T2DM and AP. …”
-
899
Supplementary file 1_Identification of glycolysis-related clusters and immune cell infiltration in hepatic fibrosis progression using machine learning models and experimental valid...
Published 2025“…Integrated weighted gene co-expression network analysis (WGCNA) with six machine learning algorithms to identify core GRGs genes associated with HF progression, and systematically characterized their biological functions and immunoregulatory roles through immune infiltration assessment, functional enrichment, consensus clustering, and single-cell differential state analysis. …”
-
900
Supplementary file 1_CYLD as a key regulator of myocardial infarction-to-heart failure transition revealed by multi-omics integration.docx
Published 2025“…Our multistep analytical pipeline included weighted gene coexpression network analysis (WGCNA) to map interacting genes, machine learning algorithms for robust classification, functional annotation via Kyoto Encyclopedia of Genes and Genomes (KEGG) to explore biological pathways, CIBERSORT correlation analysis linking hub genes with immune cell states, transcriptional regulation profiling of key hubs, and single-cell sequencing to assess the functional relevance of these hubs.…”