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algorithm python » algorithm within (Expand Search), algorithms within (Expand Search), algorithm both (Expand Search)
python function » protein function (Expand Search)
based function » based functional (Expand Search), basis function (Expand Search), basis functions (Expand Search)
algorithm etc » algorithm _ (Expand Search), algorithm b (Expand Search), algorithm a (Expand Search)
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10341
DataSheet1_Construction of a mitochondrial dysfunction related signature of diagnosed model to obstructive sleep apnea.docx
Published 2022“…Additionally, consensus clustering algorithms were used to conduct an unsupervised cluster analysis. …”
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10342
Image5_A Multi-Omics Pan-Cancer Analysis of 4EBP1 in Cancer Prognosis and Cancer-Associated Fibroblasts Infiltration.TIF
Published 2022“…</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. …”
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10343
Image1_A Multi-Omics Pan-Cancer Analysis of 4EBP1 in Cancer Prognosis and Cancer-Associated Fibroblasts Infiltration.TIF
Published 2022“…</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. …”
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10344
Table 1_Identification of regulatory cell death-related genes during MASH progression using bioinformatics analysis and machine learning strategies.xlsx
Published 2025“…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. …”
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10345
Table_1_Characterizing mitochondrial features in osteoarthritis through integrative multi-omics and machine learning analysis.docx
Published 2024“…We utilized single-sample gene set enrichment analysis (ssGSEA), gene set enrichment analysis (GSEA), and weighted gene co-expression network analysis (WGCNA) analyses to explore the functional mechanisms associated with these genes. Seven machine learning algorithms were utilized to identify hub mitochondria-related genes and develop a predictive model. …”
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10346
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...
Published 2025“…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. …”
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10347
Raw LC-MS/MS and RNA-Seq Mitochondria data
Published 2025“…Differentially altered pathways were evaluated by using the enrich plot package in R for visualization of functional enrichment (i.e., dot plot).</p>…”
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10348
<b>dGenhancer v2</b>: A software tool for designing oligonucleotides that can trigger gene-specific Enhancement of Protein Translation.
Published 2024“…<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. …”
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10349
IUTF Dataset(Enhanced): Enabling Cross-Border Resource for Analysing the Impact of Rainfall on Urban Transportation Systems
Published 2025“…</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>…”
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10350
Population trajectories for synthetic data.
Published 2023“…An essential feature of our approach is the ability to track the time-varying association between the populations while making minimal assumptions on their functional shapes via Markov random field priors. We provide nonparametric estimators, extensions of our base model that integrate multiple data sources, and fast scalable inference algorithms. …”