Image2_Identification of novel biomarkers, shared molecular signatures and immune cell infiltration in heart and kidney failure by transcriptomics.tif by 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. …”

Image1_Identification of novel biomarkers, shared molecular signatures and immune cell infiltration in heart and kidney failure by transcriptomics.tif by 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_Genetic variants and molecular profiling of 46,XY gonadal dysgenesis using whole-exome sequencing.docx by Ning Zhang (23771)

“…These variant sites are conserved among species and were predicted to be damaging according to functional algorithms and protein analyses. Additionally, 71.4% of the GATA4 amino acid changes in 46,XY GD were located in or close to the N-terminal zinc finger (N-ZF) domain. …”

DataSheet1_Identification of novel biomarkers, shared molecular signatures and immune cell infiltration in heart and kidney failure by transcriptomics.docx by 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_Multi-omics exploration of chaperone-mediated immune-proteostasis crosstalk in vascular dementia and identification of diagnostic biomarkers.xlsx by Wentong Li (492392)

“…Differentially expressed genes (DEGs) were identified using the limma package (log2FC>0.656, p<0.05). Protein-protein interaction (PPI) networks were constructed using the STRING database. …”

Data Sheet 5_Multi-omics exploration of chaperone-mediated immune-proteostasis crosstalk in vascular dementia and identification of diagnostic biomarkers.csv by Wentong Li (492392)

“…Differentially expressed genes (DEGs) were identified using the limma package (log2FC>0.656, p<0.05). Protein-protein interaction (PPI) networks were constructed using the STRING database. …”

Supplementary file 1_Multi-omics exploration of chaperone-mediated immune-proteostasis crosstalk in vascular dementia and identification of diagnostic biomarkers.docx by Wentong Li (492392)

“…Differentially expressed genes (DEGs) were identified using the limma package (log2FC>0.656, p<0.05). Protein-protein interaction (PPI) networks were constructed using the STRING database. …”

Data Sheet 2_Multi-omics exploration of chaperone-mediated immune-proteostasis crosstalk in vascular dementia and identification of diagnostic biomarkers.xlsx by Wentong Li (492392)

“…Differentially expressed genes (DEGs) were identified using the limma package (log2FC>0.656, p<0.05). Protein-protein interaction (PPI) networks were constructed using the STRING database. …”

Data Sheet 3_Multi-omics exploration of chaperone-mediated immune-proteostasis crosstalk in vascular dementia and identification of diagnostic biomarkers.xlsx by Wentong Li (492392)

“…Differentially expressed genes (DEGs) were identified using the limma package (log2FC>0.656, p<0.05). Protein-protein interaction (PPI) networks were constructed using the STRING database. …”

Data Sheet 4_Multi-omics exploration of chaperone-mediated immune-proteostasis crosstalk in vascular dementia and identification of diagnostic biomarkers.xlsx by Wentong Li (492392)

“…Differentially expressed genes (DEGs) were identified using the limma package (log2FC>0.656, p<0.05). Protein-protein interaction (PPI) networks were constructed using the STRING database. …”

Bioinformatics-based screening and experimental validation of biomarkers for the treatment of connective tissue-associated interstitial lung disease with liquorice and dried ginger... by Hui Yuan (402180)

“…</p> <p>Public datasets of Peripheral blood mononuclear cells (PBMCs) from CTD-ILD (n = 4) and connective tissue disease-associated non-Inflammatory lung disease (CTD-NILD) (n = 3) patients were analyzed using differential expression (p.adj < 0.05 & |log2 Fold Change (FC)| > 0.5), protein-protein interaction networks, and cytohubba algorithms (Top5 genes from six algorithms). …”

Image 2_Leveraging the integration of bioinformatics and machine learning to uncover common biomarkers and molecular pathways underlying diabetes and nephrolithiasis.tif by Xudong Shen (205653)

“…Functional enrichment analysis was performed, alongside the construction of protein-protein interaction (PPI) networks and transcription factor (TF)-gene interaction networks.…”

Image 3_Leveraging the integration of bioinformatics and machine learning to uncover common biomarkers and molecular pathways underlying diabetes and nephrolithiasis.tif by Xudong Shen (205653)

“…Functional enrichment analysis was performed, alongside the construction of protein-protein interaction (PPI) networks and transcription factor (TF)-gene interaction networks.…”

Image 1_Leveraging the integration of bioinformatics and machine learning to uncover common biomarkers and molecular pathways underlying diabetes and nephrolithiasis.tif by Xudong Shen (205653)

“…Functional enrichment analysis was performed, alongside the construction of protein-protein interaction (PPI) networks and transcription factor (TF)-gene interaction networks.…”

Image 4_Leveraging the integration of bioinformatics and machine learning to uncover common biomarkers and molecular pathways underlying diabetes and nephrolithiasis.tif by Xudong Shen (205653)

“…Functional enrichment analysis was performed, alongside the construction of protein-protein interaction (PPI) networks and transcription factor (TF)-gene interaction networks.…”

Supplementary file 1_Identification and validation of biomarkers in gastric cancer-associated membranous nephropathy: Insights from comprehensive bioinformatics analysis and machin... by Qianqian Xu (731060)

“…LASSO regression and Random Forest algorithms were used to identify hub genes associated with GC-related MN. …”

Table 1_Identification and validation of biomarkers in gastric cancer-associated membranous nephropathy: Insights from comprehensive bioinformatics analysis and machine learning.xl... by Qianqian Xu (731060)

“…LASSO regression and Random Forest algorithms were used to identify hub genes associated with GC-related MN. …”

Table 1_Leveraging the integration of bioinformatics and machine learning to uncover common biomarkers and molecular pathways underlying diabetes and nephrolithiasis.docx by Xudong Shen (205653)

“…Functional enrichment analysis was performed, alongside the construction of protein-protein interaction (PPI) networks and transcription factor (TF)-gene interaction networks.…”

Image 5_Leveraging the integration of bioinformatics and machine learning to uncover common biomarkers and molecular pathways underlying diabetes and nephrolithiasis.tif by Xudong Shen (205653)

“…Functional enrichment analysis was performed, alongside the construction of protein-protein interaction (PPI) networks and transcription factor (TF)-gene interaction networks.…”

Data Sheet 1_Identification and validation of biomarkers in gastric cancer-associated membranous nephropathy: Insights from comprehensive bioinformatics analysis and machine learni... by Qianqian Xu (731060)

“…LASSO regression and Random Forest algorithms were used to identify hub genes associated with GC-related MN. …”