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. …”

Data Sheet 1_Recognition of pivotal immune genes NR1H4 and IL4R as diagnostic biomarkers in distinguishing ovarian clear cell cancer from high-grade serous cancer.zip by Yumin Ke (14194880)

“…To identify differentially immune-related genes (DIRGs) linked to OCCC. We assessed DIRGs functional enrichment and built a protein-protein interaction (PPI) to explore DIRGs interactions. …”

Data Sheet 1_Tuina therapy alleviates knee osteoarthritis by modulating PI3K/AKT/mTOR-mediated autophagy: an integrated machine learning and in vivo rat study.pdf by Zhen Wang (72451)

“…A secondary analysis was conducted using a support vector machine (SVM) algorithm to predict therapeutic effects and synergistic correlations between indicators.…”

DataSheet2_Identification and validation of efferocytosis-related biomarkers for the diagnosis of metabolic dysfunction-associated steatohepatitis based on bioinformatics analysis... by Chenghui Cao (12472029)

“…This analysis was followed by a series of in-depth investigations, including protein–protein interaction (PPI), correlation analysis, and functional enrichment analysis, to uncover the molecular interactions and pathways at play. …”

Table 1_Integrated transcriptomic and network analysis reveals candidate immune–metabolic biomarkers in children with the inattentive type of ADHD.xlsx by Qiaoyan Shao (22357861)

“…High-confidence biomarkers were selected via a multi-step pipeline combining protein-protein interaction (PPI) network analysis and machine learning feature selection (LASSO regression, Boruta algorithm). …”

Data Sheet 1_Exploring the shared gene signatures and mechanism among three autoimmune diseases by bulk RNA sequencing integrated with single-cell RNA sequencing analysis.docx by Xiaofang Liu (398453)

“…Weighted Gene Co-Expression Network Analysis (WGCNA) was employed to construct gene co-expression networks and identify disease-associated modules. Functional enrichment analyses and Protein-Protein Interaction (PPI) network was constructed. …”

Image 1_Integrated transcriptomic and network analysis reveals candidate immune–metabolic biomarkers in children with the inattentive type of ADHD.tif by Qiaoyan Shao (22357861)

“…High-confidence biomarkers were selected via a multi-step pipeline combining protein-protein interaction (PPI) network analysis and machine learning feature selection (LASSO regression, Boruta algorithm). …”

Table 2_Integrated transcriptomic and network analysis reveals candidate immune–metabolic biomarkers in children with the inattentive type of ADHD.xlsx by Qiaoyan Shao (22357861)

“…High-confidence biomarkers were selected via a multi-step pipeline combining protein-protein interaction (PPI) network analysis and machine learning feature selection (LASSO regression, Boruta algorithm). …”

Table 1_Leveraging a disulfidptosis-based signature to characterize heterogeneity and optimize treatment in multiple myeloma.docx by Bingxin Zhang (13011397)

“…We further explored genetic mutation mapping, protein-protein interactions, functional enrichment, drug sensitivity, drug prediction, and immune infiltration analysis among subtypes and risk subgroups. …”

DataSheet1_Identification and validation of efferocytosis-related biomarkers for the diagnosis of metabolic dysfunction-associated steatohepatitis based on bioinformatics analysis... by Chenghui Cao (12472029)

“…This analysis was followed by a series of in-depth investigations, including protein–protein interaction (PPI), correlation analysis, and functional enrichment analysis, to uncover the molecular interactions and pathways at play. …”

Data Sheet 1_Multiple analytical perspectives of mitochondrial genes in the context of preeclampsia: potential diagnostic markers.docx by Can Li (31070)

“…Data from three datasets were integrated using the ComBat algorithm to mitigate batch effects. Differential expression analysis identified genes differentially expressed between PE cases and Control group. …”

Data Sheet 1_Deciphering macrophage differentiation and cell death dynamics in heart failure: a single-cell sequencing odyssey.zip by Jin Wei (424761)

“…Integrated differential expression analysis, protein–protein interaction network mapping, and multi-algorithm feature selection (LASSO, SVM-RFE, Random Forest) were performed, and candidate biomarkers were validated using an independent bulk RNA-seq dataset (GSE57345).…”

Table 1_Identifying pyroptosis-hub genes and immune infiltration in neonatal hypoxic-ischemic brain injury.docx by Chi Qin (10001651)

“…Immune infiltration analysis revealed that, compared to the control group, the HIBD group exhibited higher levels of innate immune cells (e.g., macrophages, M0 cells, and dendritic cells) and adaptive immune cells (e.g., CD8 naïve T cells, CD4 follicular helper T cells, and Th1 cells). The ssGSEA algorithm results indicated differences in 25 types of immune cells and 10 immune functions. …”

Data Sheet 2_Deciphering macrophage differentiation and cell death dynamics in heart failure: a single-cell sequencing odyssey.zip by Jin Wei (424761)

“…Integrated differential expression analysis, protein–protein interaction network mapping, and multi-algorithm feature selection (LASSO, SVM-RFE, Random Forest) were performed, and candidate biomarkers were validated using an independent bulk RNA-seq dataset (GSE57345).…”

Supplementary file 1_Identifying pyroptosis-hub genes and immune infiltration in neonatal hypoxic-ischemic brain injury.docx by Chi Qin (10001651)

“…Immune infiltration analysis revealed that, compared to the control group, the HIBD group exhibited higher levels of innate immune cells (e.g., macrophages, M0 cells, and dendritic cells) and adaptive immune cells (e.g., CD8 naïve T cells, CD4 follicular helper T cells, and Th1 cells). The ssGSEA algorithm results indicated differences in 25 types of immune cells and 10 immune functions. …”

Landscape17 by Vlad Carare (22092515)

“…</p><p dir="ltr">We utilized TopSearch, an open-source Python package, to perform landscape exploration, at an estimated cost of 10⁵CPUh. …”

Image 3_The osteosarcoma immune microenvironment in progression: PLEK as a prognostic biomarker and therapeutic target.tif by Yunpeng Zou (3723007)

“…</p>Methods<p>We conducted differential expression and survival analyses using OS transcriptomic datasets and TCGA/GTEx data. Protein–protein interaction networks, GO/KEGG enrichment, and CytoHubba algorithms identified core hub genes. …”

Image 2_The osteosarcoma immune microenvironment in progression: PLEK as a prognostic biomarker and therapeutic target.tif by Yunpeng Zou (3723007)

“…</p>Methods<p>We conducted differential expression and survival analyses using OS transcriptomic datasets and TCGA/GTEx data. Protein–protein interaction networks, GO/KEGG enrichment, and CytoHubba algorithms identified core hub genes. …”

Image 4_The osteosarcoma immune microenvironment in progression: PLEK as a prognostic biomarker and therapeutic target.tif by Yunpeng Zou (3723007)

“…</p>Methods<p>We conducted differential expression and survival analyses using OS transcriptomic datasets and TCGA/GTEx data. Protein–protein interaction networks, GO/KEGG enrichment, and CytoHubba algorithms identified core hub genes. …”