Interrupted Narratives: A Curatorial Laboratory on Digital Colonialism by Victor Murari (22208293)

“…</p><p><br></p><p dir="ltr">In a moment when algorithmic infrastructures increasingly regulate artistic visibility, the exhibition seeks to render perceptible the hidden architectures of data extraction, censorship, and surveillance that condition both creation and reception in the digital sphere. …”

Table 5_MMPred: a tool to predict peptide mimicry events in MHC class II recognition.xlsx by Filippo Guerri (17017524)

“…To evaluate MMPred’s ability to produce biologically meaningful insights, we conducted a comprehensive assessment involving i) predicting associations between known HLA class II human autoepitopes and microbial-peptide mimicry, ii) interpreting these predictions within a systems biology framework to identify potential functional links between the predicted autoantigens and pathophysiological pathways related to autoimmune diseases, and iii) analyzing illustrative cases in the context of SARS-CoV-2 infection and autoimmunity. …”

Table 3_MMPred: a tool to predict peptide mimicry events in MHC class II recognition.xlsx by Filippo Guerri (17017524)

“…To evaluate MMPred’s ability to produce biologically meaningful insights, we conducted a comprehensive assessment involving i) predicting associations between known HLA class II human autoepitopes and microbial-peptide mimicry, ii) interpreting these predictions within a systems biology framework to identify potential functional links between the predicted autoantigens and pathophysiological pathways related to autoimmune diseases, and iii) analyzing illustrative cases in the context of SARS-CoV-2 infection and autoimmunity. …”

Table 6_MMPred: a tool to predict peptide mimicry events in MHC class II recognition.xlsx by Filippo Guerri (17017524)

“…To evaluate MMPred’s ability to produce biologically meaningful insights, we conducted a comprehensive assessment involving i) predicting associations between known HLA class II human autoepitopes and microbial-peptide mimicry, ii) interpreting these predictions within a systems biology framework to identify potential functional links between the predicted autoantigens and pathophysiological pathways related to autoimmune diseases, and iii) analyzing illustrative cases in the context of SARS-CoV-2 infection and autoimmunity. …”

Table 2_MMPred: a tool to predict peptide mimicry events in MHC class II recognition.xlsx by Filippo Guerri (17017524)

“…To evaluate MMPred’s ability to produce biologically meaningful insights, we conducted a comprehensive assessment involving i) predicting associations between known HLA class II human autoepitopes and microbial-peptide mimicry, ii) interpreting these predictions within a systems biology framework to identify potential functional links between the predicted autoantigens and pathophysiological pathways related to autoimmune diseases, and iii) analyzing illustrative cases in the context of SARS-CoV-2 infection and autoimmunity. …”

Table 4_MMPred: a tool to predict peptide mimicry events in MHC class II recognition.xlsx by Filippo Guerri (17017524)

“…To evaluate MMPred’s ability to produce biologically meaningful insights, we conducted a comprehensive assessment involving i) predicting associations between known HLA class II human autoepitopes and microbial-peptide mimicry, ii) interpreting these predictions within a systems biology framework to identify potential functional links between the predicted autoantigens and pathophysiological pathways related to autoimmune diseases, and iii) analyzing illustrative cases in the context of SARS-CoV-2 infection and autoimmunity. …”

Table 7_MMPred: a tool to predict peptide mimicry events in MHC class II recognition.xlsx by Filippo Guerri (17017524)

“…To evaluate MMPred’s ability to produce biologically meaningful insights, we conducted a comprehensive assessment involving i) predicting associations between known HLA class II human autoepitopes and microbial-peptide mimicry, ii) interpreting these predictions within a systems biology framework to identify potential functional links between the predicted autoantigens and pathophysiological pathways related to autoimmune diseases, and iii) analyzing illustrative cases in the context of SARS-CoV-2 infection and autoimmunity. …”

Table 1_MMPred: a tool to predict peptide mimicry events in MHC class II recognition.xlsx by Filippo Guerri (17017524)

“…To evaluate MMPred’s ability to produce biologically meaningful insights, we conducted a comprehensive assessment involving i) predicting associations between known HLA class II human autoepitopes and microbial-peptide mimicry, ii) interpreting these predictions within a systems biology framework to identify potential functional links between the predicted autoantigens and pathophysiological pathways related to autoimmune diseases, and iii) analyzing illustrative cases in the context of SARS-CoV-2 infection and autoimmunity. …”

Table 8_MMPred: a tool to predict peptide mimicry events in MHC class II recognition.xlsx by Filippo Guerri (17017524)

“…To evaluate MMPred’s ability to produce biologically meaningful insights, we conducted a comprehensive assessment involving i) predicting associations between known HLA class II human autoepitopes and microbial-peptide mimicry, ii) interpreting these predictions within a systems biology framework to identify potential functional links between the predicted autoantigens and pathophysiological pathways related to autoimmune diseases, and iii) analyzing illustrative cases in the context of SARS-CoV-2 infection and autoimmunity. …”

Data_Sheet_2_Comprehensive analysis of the diagnostic and therapeutic value, immune infiltration, and drug treatment mechanisms of GTSE1 in lung adenocarcinoma.docx by Guanqiang Yan (18472116)

“…GTSE1 expression emerged as an independent predictive factor in both univariate and multivariate Cox regression analyses. …”

Table 1_Integrative machine learning and bioinformatics analysis to identify cellular senescence-related genes and potential therapeutic targets in ulcerative colitis and colorecta... by Tianle Xue (21462608)

“…The diagnostic performance of the candidate genes was evaluated using receiver operating characteristic (ROC) analyses in both training and validation cohorts. In addition, immune cell infiltration, protein–protein interaction (PPI) networks, and drug enrichment analyses—including molecular docking—were performed to further elucidate the biological functions and therapeutic potentials of the identified genes.…”

Data_Sheet_3_Comprehensive analysis of the diagnostic and therapeutic value, immune infiltration, and drug treatment mechanisms of GTSE1 in lung adenocarcinoma.docx by Guanqiang Yan (18472116)

“…GTSE1 expression emerged as an independent predictive factor in both univariate and multivariate Cox regression analyses. …”

Table 2_Integrative machine learning and bioinformatics analysis to identify cellular senescence-related genes and potential therapeutic targets in ulcerative colitis and colorecta... by Tianle Xue (21462608)

“…The diagnostic performance of the candidate genes was evaluated using receiver operating characteristic (ROC) analyses in both training and validation cohorts. In addition, immune cell infiltration, protein–protein interaction (PPI) networks, and drug enrichment analyses—including molecular docking—were performed to further elucidate the biological functions and therapeutic potentials of the identified genes.…”

Data_Sheet_1_Comprehensive analysis of the diagnostic and therapeutic value, immune infiltration, and drug treatment mechanisms of GTSE1 in lung adenocarcinoma.docx by Guanqiang Yan (18472116)

“…GTSE1 expression emerged as an independent predictive factor in both univariate and multivariate Cox regression analyses. …”

Table 3_Integrative machine learning and bioinformatics analysis to identify cellular senescence-related genes and potential therapeutic targets in ulcerative colitis and colorecta... by Tianle Xue (21462608)

“…The diagnostic performance of the candidate genes was evaluated using receiver operating characteristic (ROC) analyses in both training and validation cohorts. In addition, immune cell infiltration, protein–protein interaction (PPI) networks, and drug enrichment analyses—including molecular docking—were performed to further elucidate the biological functions and therapeutic potentials of the identified genes.…”

Data Sheet 1_Diagnostic lncRNA biomarkers and immune-related ceRNA networks for osteonecrosis of the femoral head in metabolic syndrome identified by plasma RNA sequencing and mach... by Haoyan Sun (22172911)

“…The MetS dataset from the Gene Expression Omnibus (GEO) was integrated, and weighted gene co-expression network analysis (WGCNA), functional enrichment, protein-protein interaction (PPI) network analysis, MCODE, CytoHubba-MCC, and random forest (RF) algorithms were employed to identify hub mRNAs and their associated lncRNAs. …”

A paired dataset of multi-modal MRI at 3 Tesla and 7 Tesla with manual hippocampal subfield segmentations on 7T T2-weighted images by Shuyu Li (18859198)

“…<p dir="ltr">The hippocampus, a region of critical interest within clinical neuroscience, is recognized as a complex structure comprising distinct subfields with unique functional attributes, connectivity patterns, and susceptibilities to disease. …”

Data Sheet 1_Deep learning in microbiome analysis: a comprehensive review of neural network models.pdf by Piotr Przymus (10165658)

“…These computational techniques have become essential for addressing the inherent complexity and high-dimensionality of microbiome data, which consist of different types of omics datasets. Deep learning algorithms have shown remarkable capabilities in pattern recognition, feature extraction, and predictive modeling, enabling researchers to uncover hidden relationships within microbial ecosystems. …”

Data Sheet 2_Deep learning in microbiome analysis: a comprehensive review of neural network models.pdf by Piotr Przymus (10165658)

“…These computational techniques have become essential for addressing the inherent complexity and high-dimensionality of microbiome data, which consist of different types of omics datasets. Deep learning algorithms have shown remarkable capabilities in pattern recognition, feature extraction, and predictive modeling, enabling researchers to uncover hidden relationships within microbial ecosystems. …”

Leadership at the Borders: Reimagining Organizational Development Amid Disrupted Context by Nawaf Al-Ghanem (17925863)

“…Digital infrastructures expand the capacity for cross-border collaboration yet expose organizations to vulnerabilities in cybersecurity, data ethics, and algorithmic inequality. Meanwhile, leadership within multicultural and transnational environments requires navigation across cultural and normative frontiers, demanding a shift from control to coordination, from authority to adaptability, and from hierarchy to networked influence.…”