Image 2_Characterization of cancer-related fibroblasts in bladder cancer and construction of CAFs-based bladder cancer classification: insights from single-cell and multi-omics ana... by Zhaokai Zhou (15239078)

“…</p>Materials and methods<p>Signal-cell RNA sequencing (scRNA-seq) datasets were used to identify CAF subpopulations in BLCA, and bulk RNA-seq datasets were used to construct CAFs-based BLCA classification. …”

Table 2_Comprehensive analysis of immunogenic cell death-related genes in liver ischemia-reperfusion injury.xlsx by Kai Lu (166354)

“…The RF and SVM machine learning algorithms were finally chosen to construct the models. …”

Supplementary file 1_Plasma FGF2 and YAP1 as novel biomarkers for MCI in the elderly: analysis via bioinformatics and clinical study.docx by Yejing Zhao (22123588)

“…Enzyme linked immunosorbent assay (ELISA) was used to detect plasma hub gene protein concentration. …”

Table 1_Comprehensive analysis of immunogenic cell death-related genes in liver ischemia-reperfusion injury.xlsx by Kai Lu (166354)

“…The RF and SVM machine learning algorithms were finally chosen to construct the models. …”

Table6_Analysis of immunogenic cell death in periodontitis based on scRNA-seq and bulk RNA-seq data.xlsx by Erli Wu (17785482)

“…By combining the bulk transcriptome and applying machine learning methods, we identified several potential ICD-related hub genes, which were then used to build diagnostic models. Subsequently, consensus clustering analysis was performed to identify ICD-associated subtypes, and multiple bioinformatics algorithms were used to investigate differences in immune cells and pathways between subtypes. …”

Table5_Analysis of immunogenic cell death in periodontitis based on scRNA-seq and bulk RNA-seq data.xlsx by Erli Wu (17785482)

“…By combining the bulk transcriptome and applying machine learning methods, we identified several potential ICD-related hub genes, which were then used to build diagnostic models. Subsequently, consensus clustering analysis was performed to identify ICD-associated subtypes, and multiple bioinformatics algorithms were used to investigate differences in immune cells and pathways between subtypes. …”

Table2_Analysis of immunogenic cell death in periodontitis based on scRNA-seq and bulk RNA-seq data.docx by Erli Wu (17785482)

“…By combining the bulk transcriptome and applying machine learning methods, we identified several potential ICD-related hub genes, which were then used to build diagnostic models. Subsequently, consensus clustering analysis was performed to identify ICD-associated subtypes, and multiple bioinformatics algorithms were used to investigate differences in immune cells and pathways between subtypes. …”

Table1_Analysis of immunogenic cell death in periodontitis based on scRNA-seq and bulk RNA-seq data.docx by Erli Wu (17785482)

“…By combining the bulk transcriptome and applying machine learning methods, we identified several potential ICD-related hub genes, which were then used to build diagnostic models. Subsequently, consensus clustering analysis was performed to identify ICD-associated subtypes, and multiple bioinformatics algorithms were used to investigate differences in immune cells and pathways between subtypes. …”

Table4_Analysis of immunogenic cell death in periodontitis based on scRNA-seq and bulk RNA-seq data.xlsx by Erli Wu (17785482)

“…By combining the bulk transcriptome and applying machine learning methods, we identified several potential ICD-related hub genes, which were then used to build diagnostic models. Subsequently, consensus clustering analysis was performed to identify ICD-associated subtypes, and multiple bioinformatics algorithms were used to investigate differences in immune cells and pathways between subtypes. …”

Table3_Analysis of immunogenic cell death in periodontitis based on scRNA-seq and bulk RNA-seq data.xlsx by Erli Wu (17785482)

“…By combining the bulk transcriptome and applying machine learning methods, we identified several potential ICD-related hub genes, which were then used to build diagnostic models. Subsequently, consensus clustering analysis was performed to identify ICD-associated subtypes, and multiple bioinformatics algorithms were used to investigate differences in immune cells and pathways between subtypes. …”

Supplementary file 1_Comprehensive analysis of phagocytosis regulatory genes in bladder cancer: implications for prognosis and immunotherapy.xlsx by Xueming Ma (2119150)

“…</p>Methods<p>Multi-omics data from the TCGA and GEO databases were integrated, and strict data preprocessing was carried out. A variety of algorithms and analysis techniques, such as Kaplan-Meier analysis, Cox regression analysis, and ConsensusClusterPlus clustering analysis, were used to identify PRGs related to the prognosis of bladder cancer patients, and functional analysis and clustering analysis were conducted in depth. …”

Antivirus Engines by Paul A. Gagniuc (1818325)

“…The material blends theoretical foundations with applied examples, illustrating models, algorithms, and data structures used in threat detection, thus offering a comprehensive perspective on how antivirus solutions are conceived and implemented in practice</p><p dir="ltr"><a href="https://github.com/Gagniuc/Antivirus-Engines" rel="noreferrer" target="_blank">Antivirus Engines</a>. …”

Image1_Analysis of immunogenic cell death in periodontitis based on scRNA-seq and bulk RNA-seq data.pdf by Erli Wu (17785482)

“…By combining the bulk transcriptome and applying machine learning methods, we identified several potential ICD-related hub genes, which were then used to build diagnostic models. Subsequently, consensus clustering analysis was performed to identify ICD-associated subtypes, and multiple bioinformatics algorithms were used to investigate differences in immune cells and pathways between subtypes. …”

Image2_Analysis of immunogenic cell death in periodontitis based on scRNA-seq and bulk RNA-seq data.pdf by Erli Wu (17785482)

“…By combining the bulk transcriptome and applying machine learning methods, we identified several potential ICD-related hub genes, which were then used to build diagnostic models. Subsequently, consensus clustering analysis was performed to identify ICD-associated subtypes, and multiple bioinformatics algorithms were used to investigate differences in immune cells and pathways between subtypes. …”