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. …”

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. …”

Equivalent Mutants Analysed via Deductive Verification by Serge Demeyer (5133878)

“…We therefore added three search algorithms: BinarySearch, FindLast and FindMin.</p>…”

Table 4_DEPDC1B, CDCA2, APOBEC3B, and TYMS are potential hub genes and therapeutic targets for diagnosing dialysis patients with heart failure.xlsx by Wenwu Tang (5493086)

“…In addition, we further explored potential mechanism and function of hub genes in HF of patients with MHD through GSEA, immune cell infiltration analysis, drug analysis and establishment of molecular regulatory network.…”

Table 1_DEPDC1B, CDCA2, APOBEC3B, and TYMS are potential hub genes and therapeutic targets for diagnosing dialysis patients with heart failure.xlsx by Wenwu Tang (5493086)

“…In addition, we further explored potential mechanism and function of hub genes in HF of patients with MHD through GSEA, immune cell infiltration analysis, drug analysis and establishment of molecular regulatory network.…”

Image 1_DEPDC1B, CDCA2, APOBEC3B, and TYMS are potential hub genes and therapeutic targets for diagnosing dialysis patients with heart failure.pdf by Wenwu Tang (5493086)

“…In addition, we further explored potential mechanism and function of hub genes in HF of patients with MHD through GSEA, immune cell infiltration analysis, drug analysis and establishment of molecular regulatory network.…”

Table 2_DEPDC1B, CDCA2, APOBEC3B, and TYMS are potential hub genes and therapeutic targets for diagnosing dialysis patients with heart failure.xlsx by Wenwu Tang (5493086)

“…In addition, we further explored potential mechanism and function of hub genes in HF of patients with MHD through GSEA, immune cell infiltration analysis, drug analysis and establishment of molecular regulatory network.…”

Table 3_DEPDC1B, CDCA2, APOBEC3B, and TYMS are potential hub genes and therapeutic targets for diagnosing dialysis patients with heart failure.xlsx by Wenwu Tang (5493086)

“…In addition, we further explored potential mechanism and function of hub genes in HF of patients with MHD through GSEA, immune cell infiltration analysis, drug analysis and establishment of molecular regulatory network.…”

Table 5_DEPDC1B, CDCA2, APOBEC3B, and TYMS are potential hub genes and therapeutic targets for diagnosing dialysis patients with heart failure.xlsx by Wenwu Tang (5493086)

“…In addition, we further explored potential mechanism and function of hub genes in HF of patients with MHD through GSEA, immune cell infiltration analysis, drug analysis and establishment of molecular regulatory network.…”