Data Sheet 4_The role and machine learning analysis of mitochondrial autophagy-related gene expression in lung adenocarcinoma.pdf by Binyu Wang (7375019)

“…Machine learning algorithms identified COASY, FTSJ1, and MOGS as pivotal genes. …”

Data Sheet 5_The role and machine learning analysis of mitochondrial autophagy-related gene expression in lung adenocarcinoma.zip by Binyu Wang (7375019)

“…Machine learning algorithms identified COASY, FTSJ1, and MOGS as pivotal genes. …”

Data Sheet 1_The role and machine learning analysis of mitochondrial autophagy-related gene expression in lung adenocarcinoma.zip by Binyu Wang (7375019)

“…Machine learning algorithms identified COASY, FTSJ1, and MOGS as pivotal genes. …”

Data Sheet 2_The role and machine learning analysis of mitochondrial autophagy-related gene expression in lung adenocarcinoma.pdf by Binyu Wang (7375019)

“…Machine learning algorithms identified COASY, FTSJ1, and MOGS as pivotal genes. …”

Data Sheet 3_The role and machine learning analysis of mitochondrial autophagy-related gene expression in lung adenocarcinoma.pdf by Binyu Wang (7375019)

“…Machine learning algorithms identified COASY, FTSJ1, and MOGS as pivotal genes. …”

DataSheet1_Significance of cuproptosis- related genes in the diagnosis and classification of psoriasis.PDF by Qingyuan Lin (13166349)

“…GO and KEGG enrichment analyses showed that the biological functions of CRGs were mainly related to acetyl-CoA metabolic processes, the mitochondrial matrix, and acyltransferase activity. …”

Supplementary file 1_Identification of glycolysis-related clusters and immune cell infiltration in hepatic fibrosis progression using machine learning models and experimental valid... by Guanglin Xiao (18113302)

“…Integrated weighted gene co-expression network analysis (WGCNA) with six machine learning algorithms to identify core GRGs genes associated with HF progression, and systematically characterized their biological functions and immunoregulatory roles through immune infiltration assessment, functional enrichment, consensus clustering, and single-cell differential state analysis. …”

DataSheet2_Significance of cuproptosis- related genes in the diagnosis and classification of psoriasis.PDF by Qingyuan Lin (13166349)

“…GO and KEGG enrichment analyses showed that the biological functions of CRGs were mainly related to acetyl-CoA metabolic processes, the mitochondrial matrix, and acyltransferase activity. …”

Table_1_Brief Sensory Training Narrows the Temporal Binding Window and Enhances Long-Term Multimodal Speech Perception.DOCX by Michael Zerr (7482335)

“…There are many complex algorithms our nervous system uses to construct a coherent perception. …”

Table 2_Integration of single-cell sequencing and machine learning identifies key macrophage-associated genetic signatures in lumbar disc degeneration.xlsx by Hongxing Zhang (209372)

“…</p>Methods<p>This study integrated scRNA-seq and bulk RNA-seq data to identify macrophage subpopulations in degenerative tissues and constructed co-expression modules using hdWGCNA. Functional enrichment was explored through GO, KEGG, and GSEA analyses. …”

Table 3_Identification and validation of glycolysis-related diagnostic signatures in diabetic nephropathy: a study based on integrative machine learning and single-cell sequence.xl... by Xiaoyin Wu (15279940)

“…Differentially expressed genes (DEGs) and their functional enrichments were identified. Glycolysis-related genes (GRGs) were selected by combining DEGs, weighted gene co-expression network, and glycolysis candidate genes. …”

DataSheet1_Identification of potential auxin response candidate genes for soybean rapid canopy coverage through comparative evolution and expression analysis.zip by Deisiany Ferreira Neres (10484791)

“…Further development of this and similar algorithms for defining and quantifying tissue- and phenotype-specificity in gene expression may allow expansion of diversity in valuable phenotypes in important crops.…”

Table_4_Analysis and Experimental Validation of Rheumatoid Arthritis Innate Immunity Gene CYFIP2 and Pan-Cancer.xls by ZhenYu Zhao (13028649)

“…For RA-related differential genes, we performed functional enrichment analysis and constructed a weighted gene co-expression network (WGCNA). …”

Table_3_Analysis and Experimental Validation of Rheumatoid Arthritis Innate Immunity Gene CYFIP2 and Pan-Cancer.csv by ZhenYu Zhao (13028649)

“…For RA-related differential genes, we performed functional enrichment analysis and constructed a weighted gene co-expression network (WGCNA). …”

Table_5_Analysis and Experimental Validation of Rheumatoid Arthritis Innate Immunity Gene CYFIP2 and Pan-Cancer.xls by ZhenYu Zhao (13028649)

“…For RA-related differential genes, we performed functional enrichment analysis and constructed a weighted gene co-expression network (WGCNA). …”

DataSheet1_Comprehensive analysis of cuproptosis-related lncRNAs to predict prognosis and immune infiltration characteristics in colorectal cancer.docx by Zhonglin Zhu (7303340)

“…The immune activate pathways, immune infiltration cells, immune functions, immune score and immune activation genes were remarkably enriched in the high risk group. …”

Table_1_Analysis and Experimental Validation of Rheumatoid Arthritis Innate Immunity Gene CYFIP2 and Pan-Cancer.doc by ZhenYu Zhao (13028649)

“…For RA-related differential genes, we performed functional enrichment analysis and constructed a weighted gene co-expression network (WGCNA). …”

Table 2_Identification and validation of glycolysis-related diagnostic signatures in diabetic nephropathy: a study based on integrative machine learning and single-cell sequence.xl... by Xiaoyin Wu (15279940)

“…Differentially expressed genes (DEGs) and their functional enrichments were identified. Glycolysis-related genes (GRGs) were selected by combining DEGs, weighted gene co-expression network, and glycolysis candidate genes. …”

Table 1_Identification and validation of key biomarkers of the glycolysis-ketone body metabolism in heart failure based on multi-omics and machine learning.xlsx by Na Xiao (327834)

“…Differentially expressed genes (DEGs) were identified and analyzed through Weighted Gene Co-expression Network Analysis (WGCNA). Candidate genes were refined using machine learning algorithms (LASSO regression and Boruta), with functional enrichment assessed via Gene Set Enrichment Analysis (GSEA). …”

Image 1_Identification and validation of key biomarkers of the glycolysis-ketone body metabolism in heart failure based on multi-omics and machine learning.pdf by Na Xiao (327834)

“…Differentially expressed genes (DEGs) were identified and analyzed through Weighted Gene Co-expression Network Analysis (WGCNA). Candidate genes were refined using machine learning algorithms (LASSO regression and Boruta), with functional enrichment assessed via Gene Set Enrichment Analysis (GSEA). …”