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1781
Image 2_Identification of ferroptosis-genes associated with pediatric inflammatory bowel disease bioinformatics and machine learning approaches.tif
Published 2025“…</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. …”
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1782
Table 5_Identification of ferroptosis-genes associated with pediatric inflammatory bowel disease bioinformatics and machine learning approaches.xlsx
Published 2025“…</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. …”
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1783
Table 7_Identification of ferroptosis-genes associated with pediatric inflammatory bowel disease bioinformatics and machine learning approaches.xlsx
Published 2025“…</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. …”
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1784
Table 2_Identification of ferroptosis-genes associated with pediatric inflammatory bowel disease bioinformatics and machine learning approaches.docx
Published 2025“…</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. …”
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1785
Table 4_Identification of ferroptosis-genes associated with pediatric inflammatory bowel disease bioinformatics and machine learning approaches.xlsx
Published 2025“…</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. …”
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1786
Table 1_Identification of ferroptosis-genes associated with pediatric inflammatory bowel disease bioinformatics and machine learning approaches.xlsx
Published 2025“…</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. …”
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1787
Image 3_Integrated multi-omics elucidates PRNP knockdown-mediated chemosensitization to gemcitabine in pancreatic ductal adenocarcinoma.tif
Published 2025“…</p>Results<p>Our findings identify the prion protein gene (PRNP) as a key gene associated with chemoresistance. …”
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1788
Image 2_Integrated multi-omics elucidates PRNP knockdown-mediated chemosensitization to gemcitabine in pancreatic ductal adenocarcinoma.tif
Published 2025“…</p>Results<p>Our findings identify the prion protein gene (PRNP) as a key gene associated with chemoresistance. …”
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1789
Table 6_Identification of ferroptosis-genes associated with pediatric inflammatory bowel disease bioinformatics and machine learning approaches.xlsx
Published 2025“…</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. …”
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1790
Image 4_Identification of ferroptosis-genes associated with pediatric inflammatory bowel disease bioinformatics and machine learning approaches.tif
Published 2025“…</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. …”
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1791
Table 3_Identification of ferroptosis-genes associated with pediatric inflammatory bowel disease bioinformatics and machine learning approaches.xlsx
Published 2025“…</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. …”
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1792
Image 3_Identification of ferroptosis-genes associated with pediatric inflammatory bowel disease bioinformatics and machine learning approaches.tif
Published 2025“…</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. …”
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1793
Image 4_Identification of three T cell-related genes as diagnostic and prognostic biomarkers for triple-negative breast cancer and exploration of potential mechanisms.tif
Published 2025“…</p>Conclusion<p>CACNA1H, KCNJ11, and S100B are potential diagnostic and prognostic biomarkers in TNBC. …”
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1794
Image 3_Identification of three T cell-related genes as diagnostic and prognostic biomarkers for triple-negative breast cancer and exploration of potential mechanisms.tif
Published 2025“…</p>Conclusion<p>CACNA1H, KCNJ11, and S100B are potential diagnostic and prognostic biomarkers in TNBC. …”
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1795
Table 1_Identification of three T cell-related genes as diagnostic and prognostic biomarkers for triple-negative breast cancer and exploration of potential mechanisms.xlsx
Published 2025“…</p>Conclusion<p>CACNA1H, KCNJ11, and S100B are potential diagnostic and prognostic biomarkers in TNBC. …”
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1796
Image 1_Identification of three T cell-related genes as diagnostic and prognostic biomarkers for triple-negative breast cancer and exploration of potential mechanisms.tif
Published 2025“…</p>Conclusion<p>CACNA1H, KCNJ11, and S100B are potential diagnostic and prognostic biomarkers in TNBC. …”
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1797
Table 3_Identification of three T cell-related genes as diagnostic and prognostic biomarkers for triple-negative breast cancer and exploration of potential mechanisms.xlsx
Published 2025“…</p>Conclusion<p>CACNA1H, KCNJ11, and S100B are potential diagnostic and prognostic biomarkers in TNBC. …”
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1798
Table 4_Identification of three T cell-related genes as diagnostic and prognostic biomarkers for triple-negative breast cancer and exploration of potential mechanisms.xlsx
Published 2025“…</p>Conclusion<p>CACNA1H, KCNJ11, and S100B are potential diagnostic and prognostic biomarkers in TNBC. …”
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1799
Table 2_Identification of three T cell-related genes as diagnostic and prognostic biomarkers for triple-negative breast cancer and exploration of potential mechanisms.xlsx
Published 2025“…</p>Conclusion<p>CACNA1H, KCNJ11, and S100B are potential diagnostic and prognostic biomarkers in TNBC. …”
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1800
Image 2_Identification of three T cell-related genes as diagnostic and prognostic biomarkers for triple-negative breast cancer and exploration of potential mechanisms.tif
Published 2025“…</p>Conclusion<p>CACNA1H, KCNJ11, and S100B are potential diagnostic and prognostic biomarkers in TNBC. …”