Table 1_Identification and validation of immune and diagnostic biomarkers for interstitial cystitis/painful bladder syndrome by integrating bioinformatics and machine-learning.docx by Tao Zhou (117050)

“…Hub genes in IC/BPS patients were identified through the application of three distinct machine-learning algorithms. Additionally, the inflammatory status and immune landscape of IC/BPS patients were evaluated using the ssGSEA algorithm. …”

Data Sheet 1_Identification of key biomarkers related to fibrocartilage chondrocytes for osteoarthritis based on bulk, single-cell transcriptomic data.docx by Bailin Pan (20300112)

“…Microarray data were integrated to identify differentially expressed genes (DEGs). We conducted functional-enrichment analyses, including Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO), and used weighted gene co-expression network analysis (WGCNA) and the least absolute shrinkage and selection operator (LASSO) algorithm to select biomarkers. …”

Data Sheet 2_Identification of key biomarkers related to fibrocartilage chondrocytes for osteoarthritis based on bulk, single-cell transcriptomic data.csv by Bailin Pan (20300112)

“…Microarray data were integrated to identify differentially expressed genes (DEGs). We conducted functional-enrichment analyses, including Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO), and used weighted gene co-expression network analysis (WGCNA) and the least absolute shrinkage and selection operator (LASSO) algorithm to select biomarkers. …”

Table 1_A novel prognostic signature identifies MFAP4 as a tumor suppressor linking the tumor microenvironment to PI3K/AKT signaling in triple-negative breast cancer.docx by Xiaoqin Yu (3918377)

“…The model’s association with TME characteristics was assessed using ESTIMATE algorithm and immune infiltration analyses. The biological functions of the key gene, Microfibril Associated Protein 4 (MFAP4), were investigated in vitro via proliferation and migration assays. …”

Table 2_A novel prognostic signature identifies MFAP4 as a tumor suppressor linking the tumor microenvironment to PI3K/AKT signaling in triple-negative breast cancer.xlsx by Xiaoqin Yu (3918377)

“…The model’s association with TME characteristics was assessed using ESTIMATE algorithm and immune infiltration analyses. The biological functions of the key gene, Microfibril Associated Protein 4 (MFAP4), were investigated in vitro via proliferation and migration assays. …”

Data Sheet 1_A novel prognostic signature identifies MFAP4 as a tumor suppressor linking the tumor microenvironment to PI3K/AKT signaling in triple-negative breast cancer.pdf by Xiaoqin Yu (3918377)

“…The model’s association with TME characteristics was assessed using ESTIMATE algorithm and immune infiltration analyses. The biological functions of the key gene, Microfibril Associated Protein 4 (MFAP4), were investigated in vitro via proliferation and migration assays. …”

Table 1_The analysis of gene co-expression network and immune infiltration revealed biomarkers between triple-negative and non-triple negative breast cancer.xlsx by Yao Yi (459571)

“…CIBERSORT analysis was used to characterize the composition of immune cells within complex tissues based on gene expression data, typically derived from bulk RNA sequencing or microarray datasets. …”

Image 1_The analysis of gene co-expression network and immune infiltration revealed biomarkers between triple-negative and non-triple negative breast cancer.tif by Yao Yi (459571)

“…CIBERSORT analysis was used to characterize the composition of immune cells within complex tissues based on gene expression data, typically derived from bulk RNA sequencing or microarray datasets. …”

Image 3_The analysis of gene co-expression network and immune infiltration revealed biomarkers between triple-negative and non-triple negative breast cancer.tif by Yao Yi (459571)

“…CIBERSORT analysis was used to characterize the composition of immune cells within complex tissues based on gene expression data, typically derived from bulk RNA sequencing or microarray datasets. …”

Image 2_The analysis of gene co-expression network and immune infiltration revealed biomarkers between triple-negative and non-triple negative breast cancer.tif by Yao Yi (459571)

“…CIBERSORT analysis was used to characterize the composition of immune cells within complex tissues based on gene expression data, typically derived from bulk RNA sequencing or microarray datasets. …”

Table 2_The analysis of gene co-expression network and immune infiltration revealed biomarkers between triple-negative and non-triple negative breast cancer.xlsx by Yao Yi (459571)

“…CIBERSORT analysis was used to characterize the composition of immune cells within complex tissues based on gene expression data, typically derived from bulk RNA sequencing or microarray datasets. …”

Table 3_The analysis of gene co-expression network and immune infiltration revealed biomarkers between triple-negative and non-triple negative breast cancer.xlsx by Yao Yi (459571)

“…CIBERSORT analysis was used to characterize the composition of immune cells within complex tissues based on gene expression data, typically derived from bulk RNA sequencing or microarray datasets. …”

Image 4_The analysis of gene co-expression network and immune infiltration revealed biomarkers between triple-negative and non-triple negative breast cancer.tif by Yao Yi (459571)

“…CIBERSORT analysis was used to characterize the composition of immune cells within complex tissues based on gene expression data, typically derived from bulk RNA sequencing or microarray datasets. …”

Image 1_Targeting a distinct binding pocket in the pregnane X receptor with natural agonist TRLW-2 ameliorates murine ulcerative colitis.tif by Shangrui Rao (18189241)

“…</p>Methods<p>A distinct binding pocket (Pocket 1–5) within the PXR ligand-binding domain was identified using a multi-algorithm computational approach (SiteMap, Fpocket, Prank, CASTpFold). …”

Image 2_Targeting a distinct binding pocket in the pregnane X receptor with natural agonist TRLW-2 ameliorates murine ulcerative colitis.tif by Shangrui Rao (18189241)

“…</p>Methods<p>A distinct binding pocket (Pocket 1–5) within the PXR ligand-binding domain was identified using a multi-algorithm computational approach (SiteMap, Fpocket, Prank, CASTpFold). …”

Image 3_Targeting a distinct binding pocket in the pregnane X receptor with natural agonist TRLW-2 ameliorates murine ulcerative colitis.tif by Shangrui Rao (18189241)

“…</p>Methods<p>A distinct binding pocket (Pocket 1–5) within the PXR ligand-binding domain was identified using a multi-algorithm computational approach (SiteMap, Fpocket, Prank, CASTpFold). …”

Image 4_Targeting a distinct binding pocket in the pregnane X receptor with natural agonist TRLW-2 ameliorates murine ulcerative colitis.tif by Shangrui Rao (18189241)

“…</p>Methods<p>A distinct binding pocket (Pocket 1–5) within the PXR ligand-binding domain was identified using a multi-algorithm computational approach (SiteMap, Fpocket, Prank, CASTpFold). …”

Additional data for the polyanion sodium cathode materials dataset by Martin Hoffmann Petersen (13626778)

“…All simulations are executed within the canonical (NVT) ensemble and a sample frequency was set to 1fs.…”

Data Sheet 1_TGM2 regulated by transcription factor NR3C1 drives p38 MAPK-mediated tumor progression and immune evasion in lung squamous cell carcinoma.zip by Chunlong Lin (18931437)

“…Key genes were screened via random forest algorithm. Functional validation was performed in NCI-H520 and SK-MES-1 cell lines. …”

Supporting data for "Machine learning based prognosis prediction of intracerebral hemorrhage outcome". by Eunhye Yang (17853260)

“…The resulting prognosis prediction ML model, based on Random Forest algorithm, achieved an overall accuracy of 0.81, with AUROCs of 0.93, 0.84 and 0.95 for good, poor, and death outcomes, respectively. …”