Image2_A Multi-Omics Pan-Cancer Analysis of 4EBP1 in Cancer Prognosis and Cancer-Associated Fibroblasts Infiltration.TIF by Kunpeng Du (10433565)

“…</p><p>Methods: In this study, we provided a multi-Omics investigation for the prognostic value of 4EBP1 mRNA, 4EBP1 protein, and different 4EBP1 phosphoproteins in a Pan-cancer manner based on the TCGA projects. We explored the correlation between 4EBP1 expression and the cancer-associated fibroblast (CAFs) infiltration, respectively using the EPIC, MCPCOUNTER, and TIDE algorithms. …”

Image4_A Multi-Omics Pan-Cancer Analysis of 4EBP1 in Cancer Prognosis and Cancer-Associated Fibroblasts Infiltration.TIF by Kunpeng Du (10433565)

“…</p><p>Methods: In this study, we provided a multi-Omics investigation for the prognostic value of 4EBP1 mRNA, 4EBP1 protein, and different 4EBP1 phosphoproteins in a Pan-cancer manner based on the TCGA projects. We explored the correlation between 4EBP1 expression and the cancer-associated fibroblast (CAFs) infiltration, respectively using the EPIC, MCPCOUNTER, and TIDE algorithms. …”

Image4_Construction of a mitochondrial dysfunction related signature of diagnosed model to obstructive sleep apnea.TIF by Qian Liu (135614)

“…Additionally, consensus clustering algorithms were used to conduct an unsupervised cluster analysis. …”

Image1_Construction of a mitochondrial dysfunction related signature of diagnosed model to obstructive sleep apnea.TIF by Qian Liu (135614)

“…Additionally, consensus clustering algorithms were used to conduct an unsupervised cluster analysis. …”

Image3_A Multi-Omics Pan-Cancer Analysis of 4EBP1 in Cancer Prognosis and Cancer-Associated Fibroblasts Infiltration.TIF by Kunpeng Du (10433565)

“…</p><p>Methods: In this study, we provided a multi-Omics investigation for the prognostic value of 4EBP1 mRNA, 4EBP1 protein, and different 4EBP1 phosphoproteins in a Pan-cancer manner based on the TCGA projects. We explored the correlation between 4EBP1 expression and the cancer-associated fibroblast (CAFs) infiltration, respectively using the EPIC, MCPCOUNTER, and TIDE algorithms. …”

Image3_Construction of a mitochondrial dysfunction related signature of diagnosed model to obstructive sleep apnea.TIF by Qian Liu (135614)

“…Additionally, consensus clustering algorithms were used to conduct an unsupervised cluster analysis. …”

Image2_Construction of a mitochondrial dysfunction related signature of diagnosed model to obstructive sleep apnea.TIF by Qian Liu (135614)

“…Additionally, consensus clustering algorithms were used to conduct an unsupervised cluster analysis. …”

Table 2_Identification of regulatory cell death-related genes during MASH progression using bioinformatics analysis and machine learning strategies.xlsx by Zhiqiang Lin (747094)

“…A total of 101 combinations of 10 machine learning algorithms were employed to screen for characteristic RCD-related differentially expressed genes (DEGs) that reflect the progression of MASH. …”

Table1_A Multi-Omics Pan-Cancer Analysis of 4EBP1 in Cancer Prognosis and Cancer-Associated Fibroblasts Infiltration.docx by Kunpeng Du (10433565)

“…</p><p>Methods: In this study, we provided a multi-Omics investigation for the prognostic value of 4EBP1 mRNA, 4EBP1 protein, and different 4EBP1 phosphoproteins in a Pan-cancer manner based on the TCGA projects. We explored the correlation between 4EBP1 expression and the cancer-associated fibroblast (CAFs) infiltration, respectively using the EPIC, MCPCOUNTER, and TIDE algorithms. …”

Image5_Construction of a mitochondrial dysfunction related signature of diagnosed model to obstructive sleep apnea.TIF by Qian Liu (135614)

“…Additionally, consensus clustering algorithms were used to conduct an unsupervised cluster analysis. …”

DataSheet1_Construction of a mitochondrial dysfunction related signature of diagnosed model to obstructive sleep apnea.docx by Qian Liu (135614)

“…Additionally, consensus clustering algorithms were used to conduct an unsupervised cluster analysis. …”

Image5_A Multi-Omics Pan-Cancer Analysis of 4EBP1 in Cancer Prognosis and Cancer-Associated Fibroblasts Infiltration.TIF by Kunpeng Du (10433565)

“…</p><p>Methods: In this study, we provided a multi-Omics investigation for the prognostic value of 4EBP1 mRNA, 4EBP1 protein, and different 4EBP1 phosphoproteins in a Pan-cancer manner based on the TCGA projects. We explored the correlation between 4EBP1 expression and the cancer-associated fibroblast (CAFs) infiltration, respectively using the EPIC, MCPCOUNTER, and TIDE algorithms. …”

Image1_A Multi-Omics Pan-Cancer Analysis of 4EBP1 in Cancer Prognosis and Cancer-Associated Fibroblasts Infiltration.TIF by Kunpeng Du (10433565)

“…</p><p>Methods: In this study, we provided a multi-Omics investigation for the prognostic value of 4EBP1 mRNA, 4EBP1 protein, and different 4EBP1 phosphoproteins in a Pan-cancer manner based on the TCGA projects. We explored the correlation between 4EBP1 expression and the cancer-associated fibroblast (CAFs) infiltration, respectively using the EPIC, MCPCOUNTER, and TIDE algorithms. …”

Table 1_Identification of regulatory cell death-related genes during MASH progression using bioinformatics analysis and machine learning strategies.xlsx by Zhiqiang Lin (747094)

“…A total of 101 combinations of 10 machine learning algorithms were employed to screen for characteristic RCD-related differentially expressed genes (DEGs) that reflect the progression of MASH. …”

Data Sheet 1_Resveratrol contributes to NK cell-mediated breast cancer cytotoxicity by upregulating ULBP2 through miR-17-5p downmodulation and activation of MINK1/JNK/c-Jun signali... by Bisha Ding (5803799)

“…UL16-binding protein 2 (ULBP2), always expressed or elevated on cancer cells, functions as a key NKG2D ligand. ULBP2-NKG2D ligation initiates NK cell activation and subsequent targeted elimination of cancer cells. …”

Raw LC-MS/MS and RNA-Seq Mitochondria data by Stefano Martellucci (16284377)

“…Differentially altered pathways were evaluated by using the enrich plot package in R for visualization of functional enrichment (i.e., dot plot).</p>…”

<b>dGenhancer v2</b>: A software tool for designing oligonucleotides that can trigger gene-specific Enhancement of Protein Translation. by Adam Master (20316450)

“…<p dir="ltr"> Software tool designed to calculate 5’UTR properties, enabling the creation of oligonucleotides that can trigger gene-specific enhancement of protein translation.<br> An excel-based calculator - dGenhancer can be used to search for putative 5’UTR cis-acting elements, which functional activity could be determined by Gibbs energy-dependent secondary structure formation. …”

IUTF Dataset(Enhanced): Enabling Cross-Border Resource for Analysing the Impact of Rainfall on Urban Transportation Systems by Xuhui Lin (19505503)

“…</p><h2>Data Structure</h2><p dir="ltr">The dataset is organized into four primary components:</p><ol><li><b>Road Network Data</b>: Topological representations including spatial geometry, functional classification, and connectivity information</li><li><b>Traffic Sensor Data</b>: Sensor metadata, locations, and measurements at both 5-minute and hourly resolutions</li><li><b>Precipitation Data</b>: Hourly meteorological information with spatial grid cell metadata</li><li><b>Derived Analytical Matrices</b>: Pre-computed structures for advanced spatial-temporal modelling and network analyses</li></ol><h2>File Formats</h2><ul><li><b>Tabular Data</b>: Apache Parquet format for optimal compression and fast query performance</li><li><b>Numerical Matrices</b>: NumPy NPZ format for efficient scientific computing</li><li><b>Total Size</b>: Approximately 2 GB uncompressed</li></ul><h2>Applications</h2><p dir="ltr">The IUTF dataset enables diverse analytical applications including:</p><ul><li><b>Traffic Flow Prediction</b>: Developing weather-aware traffic forecasting models</li><li><b>Infrastructure Planning</b>: Identifying vulnerable network components and prioritizing investments</li><li><b>Resilience Assessment</b>: Quantifying system recovery curves, robustness metrics, and adaptive capacity</li><li><b>Climate Adaptation</b>: Supporting evidence-based transportation planning under changing precipitation patterns</li><li><b>Emergency Management</b>: Improving response strategies for weather-related traffic disruptions</li></ul><h2>Methodology</h2><p dir="ltr">The dataset creation involved three main stages:</p><ol><li><b>Data Collection</b>: Sourcing traffic data from UTD19, road networks from OpenStreetMap, and precipitation data from ERA5 reanalysis</li><li><b>Spatio-Temporal Harmonization</b>: Comprehensive integration using novel algorithms for spatial alignment and temporal synchronization</li><li><b>Quality Assurance</b>: Rigorous validation and technical verification across all cities and data components</li></ol><h2>Code Availability</h2><p dir="ltr">Processing code is available at: https://github.com/viviRG2024/IUTDF_processing</p>…”