Image 1_Integrated transcriptomic and single-cell RNA-seq analysis identifies CLCNKB, KLK1 and PLEKHA4 as key gene of AKI-to-CKD progression.tif by Fanhua Zeng (2097133)

“…Biomarkers were subsequently identified using machine learning algorithms, receiver operating characteristic curve analysis, expression analysis and experimental verification. …”

Gene expression omnibus datasets. by Xinyi Xia (7516694)

“…Three machine learning algorithms screened for hub genes, which underwent miRNA prediction and transcription factor analysis. …”

Image 1_Dysregulated arginine metabolism is associated with pro-tumor neutrophil polarization in liver cancer.tif by Xingchao Liu (3501161)

“…Intercellular communication was analyzed using CellChat, while machine learning, incorporating seven different algorithms, was applied to identify key regulatory genes.…”

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 by Zhi-Chuan He (21563657)

“…Differentially expressed genes (DEGs) between TNBC and other BRCA subtypes were intersected with T cell-related genes to identify candidate biomarkers. Machine learning algorithms were used to screen for key hub genes, which were then used to construct a logistic regression (LR) model. …”

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 by Zhi-Chuan He (21563657)

“…Differentially expressed genes (DEGs) between TNBC and other BRCA subtypes were intersected with T cell-related genes to identify candidate biomarkers. Machine learning algorithms were used to screen for key hub genes, which were then used to construct a logistic regression (LR) model. …”

Table 1_Integrated transcriptomic and single-cell RNA-seq analysis identifies CLCNKB, KLK1 and PLEKHA4 as key gene of AKI-to-CKD progression.xlsx by Fanhua Zeng (2097133)

“…Biomarkers were subsequently identified using machine learning algorithms, receiver operating characteristic curve analysis, expression analysis and experimental verification. …”

Image 6_Dysregulated arginine metabolism is associated with pro-tumor neutrophil polarization in liver cancer.tif by Xingchao Liu (3501161)

“…Intercellular communication was analyzed using CellChat, while machine learning, incorporating seven different algorithms, was applied to identify key regulatory genes.…”

Table 1_Metabolic-stem cell crosstalk in PD: NK1 cells as key mediators from a bioinformatics perspective.xlsx by Junxin Zhao (16721864)

“…Our analytical workflow entailed: differential expression screening, functional enrichment, protein–protein interaction (PPI) network construction, and machine learning (ML) algorithms.…”

Data Sheet 1_Metabolic-stem cell crosstalk in PD: NK1 cells as key mediators from a bioinformatics perspective.pdf by Junxin Zhao (16721864)

“…Our analytical workflow entailed: differential expression screening, functional enrichment, protein–protein interaction (PPI) network construction, and machine learning (ML) algorithms.…”

Image 4_Identification of lactylation-related biomarkers in osteoporosis from transcriptome and single-cell data.jpeg by Jiafeng Peng (22116253)

“…First, the biomarkers associated with OP were identified through differential gene expression analysis, machine learning algorithms, expression validation, and receiver operating characteristic (ROC) curve analysis. …”

Table 4_Identification of lactylation-related biomarkers in osteoporosis from transcriptome and single-cell data.xlsx by Jiafeng Peng (22116253)

“…First, the biomarkers associated with OP were identified through differential gene expression analysis, machine learning algorithms, expression validation, and receiver operating characteristic (ROC) curve analysis. …”

Image 2_Identification of lactylation-related biomarkers in osteoporosis from transcriptome and single-cell data.tif by Jiafeng Peng (22116253)

“…First, the biomarkers associated with OP were identified through differential gene expression analysis, machine learning algorithms, expression validation, and receiver operating characteristic (ROC) curve analysis. …”

Table 5_Identification of lactylation-related biomarkers in osteoporosis from transcriptome and single-cell data.xlsx by Jiafeng Peng (22116253)

“…First, the biomarkers associated with OP were identified through differential gene expression analysis, machine learning algorithms, expression validation, and receiver operating characteristic (ROC) curve analysis. …”

Image 1_Identification of lactylation-related biomarkers in osteoporosis from transcriptome and single-cell data.tif by Jiafeng Peng (22116253)

“…First, the biomarkers associated with OP were identified through differential gene expression analysis, machine learning algorithms, expression validation, and receiver operating characteristic (ROC) curve analysis. …”

Table 3_Identification of lactylation-related biomarkers in osteoporosis from transcriptome and single-cell data.docx by Jiafeng Peng (22116253)

“…First, the biomarkers associated with OP were identified through differential gene expression analysis, machine learning algorithms, expression validation, and receiver operating characteristic (ROC) curve analysis. …”

Table 7_Identification of lactylation-related biomarkers in osteoporosis from transcriptome and single-cell data.xlsx by Jiafeng Peng (22116253)

“…First, the biomarkers associated with OP were identified through differential gene expression analysis, machine learning algorithms, expression validation, and receiver operating characteristic (ROC) curve analysis. …”

Image 6_Identification of lactylation-related biomarkers in osteoporosis from transcriptome and single-cell data.jpeg by Jiafeng Peng (22116253)

“…First, the biomarkers associated with OP were identified through differential gene expression analysis, machine learning algorithms, expression validation, and receiver operating characteristic (ROC) curve analysis. …”

Table 1_Identification of lactylation-related biomarkers in osteoporosis from transcriptome and single-cell data.xlsx by Jiafeng Peng (22116253)

“…First, the biomarkers associated with OP were identified through differential gene expression analysis, machine learning algorithms, expression validation, and receiver operating characteristic (ROC) curve analysis. …”

Table 2_Identification of lactylation-related biomarkers in osteoporosis from transcriptome and single-cell data.docx by Jiafeng Peng (22116253)

“…First, the biomarkers associated with OP were identified through differential gene expression analysis, machine learning algorithms, expression validation, and receiver operating characteristic (ROC) curve analysis. …”

Table 8_Identification of lactylation-related biomarkers in osteoporosis from transcriptome and single-cell data.xlsx by Jiafeng Peng (22116253)

“…First, the biomarkers associated with OP were identified through differential gene expression analysis, machine learning algorithms, expression validation, and receiver operating characteristic (ROC) curve analysis. …”