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721
Enrichment analysis of GO.
Published 2025“…We also identified differentially expressed genes (DEGs) within the clusters and between SLE patients and healthy controls. …”
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722
Differential gene expression analysis results.
Published 2025“…We also identified differentially expressed genes (DEGs) within the clusters and between SLE patients and healthy controls. …”
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723
The flowchart of this study.
Published 2025“…We also identified differentially expressed genes (DEGs) within the clusters and between SLE patients and healthy controls. …”
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724
DGIdb.
Published 2025“…We also identified differentially expressed genes (DEGs) within the clusters and between SLE patients and healthy controls. …”
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725
Etodolac utility in osteoarthritis: drug delivery challenges, topical nanotherapeutic strategies and potential synergies
Published 2024“…Inflammatory processes within OSA joints are regulated by pro-inflammatory and anti-inflammatory cytokines. …”
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726
Glucocorticoid related genes.
Published 2025“…We also identified differentially expressed genes (DEGs) within the clusters and between SLE patients and healthy controls. …”
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727
CIBERSORTx results.
Published 2025“…We also identified differentially expressed genes (DEGs) within the clusters and between SLE patients and healthy controls. …”
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728
Differential gene expression analysis results.
Published 2025“…We also identified differentially expressed genes (DEGs) within the clusters and between SLE patients and healthy controls. …”
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729
GSEA result.
Published 2025“…We also identified differentially expressed genes (DEGs) within the clusters and between SLE patients and healthy controls. …”
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730
Enrichment analysis of GO.
Published 2025“…We also identified differentially expressed genes (DEGs) within the clusters and between SLE patients and healthy controls. …”
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731
Lasso gene RF hub gene.
Published 2025“…We also identified differentially expressed genes (DEGs) within the clusters and between SLE patients and healthy controls. …”
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732
Enrichment analysis of KEGG.
Published 2025“…We also identified differentially expressed genes (DEGs) within the clusters and between SLE patients and healthy controls. …”
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733
Image 1_Characterization of cancer-related fibroblasts in bladder cancer and construction of CAFs-based bladder cancer classification: insights from single-cell and multi-omics ana...
Published 2025“…Moreover, machine learning algorithms were applied to identify novel potential targets for each subtype, and experimentally validate their effects.…”
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734
Table 1_Characterization of cancer-related fibroblasts in bladder cancer and construction of CAFs-based bladder cancer classification: insights from single-cell and multi-omics ana...
Published 2025“…Moreover, machine learning algorithms were applied to identify novel potential targets for each subtype, and experimentally validate their effects.…”
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735
Image 2_Characterization of cancer-related fibroblasts in bladder cancer and construction of CAFs-based bladder cancer classification: insights from single-cell and multi-omics ana...
Published 2025“…Moreover, machine learning algorithms were applied to identify novel potential targets for each subtype, and experimentally validate their effects.…”
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736
Raw LC-MS/MS and RNA-Seq Mitochondria data
Published 2025“…Differentially altered pathways were evaluated by using the enrich plot package in R for visualization of functional enrichment (i.e., dot plot).</p>…”
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737
DataSheet1_Mitochondrial-related genes as prognostic and metastatic markers in breast cancer: insights from comprehensive analysis and clinical models.docx
Published 2024“…Moreover, leveraging the GSE102484 dataset, we conducted differential gene expression analysis to identify MRGs related to metastasis, subsequently developing metastasis models via 10 distinct machine-learning algorithms and then selecting the best-performing model. …”
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738
Table1_Mitochondrial-related genes as prognostic and metastatic markers in breast cancer: insights from comprehensive analysis and clinical models.xlsx
Published 2024“…Moreover, leveraging the GSE102484 dataset, we conducted differential gene expression analysis to identify MRGs related to metastasis, subsequently developing metastasis models via 10 distinct machine-learning algorithms and then selecting the best-performing model. …”