Albumin Degradome Foundation Atlas حسب Axel Petzold (7076261)

"…</p><h2><b>Data Format and Access</b></h2><ul><li><b>Primary file:</b> <code>Albumin_Degradome_Foundation_Atlas_v1.tar.xz</code><br>(contains all peptide tables in standard CSV format)</li><li><b>File Type:</b> ASCII comma-separated values (CSV)</li><li><b>Compression:</b> <code>xz -9 -T0</code> for maximal CPU-parallelised compression</li><li><b>Compatibility:</b></li><li><ul><li>R, Python, MATLAB, SAS</li><li>Excel, LibreOffice</li><li>Any proteomics workflow (e.g., Skyline, MaxQuant preprocessing, MS/MS spectral libraries)</li></ul></li></ul><h2><b>FAIR Principles</b></h2><p dir="ltr">This dataset is fully aligned with FAIR data standards:</p><ul><li><b>Findable:</b> Rich metadata, stable DOI, search-optimised description</li><li><b>Accessible:</b> Open-access Figshare repository</li><li><b>Interoperable:</b> Standard numeric and CSV formats</li><li><b>Reusable:</b> Transparent, reproducible Python source code included</li></ul><h2><b>Applications</b></h2><p dir="ltr">The Albumin Degradome Foundation Atlas supports research across multiple biomedical domains:</p><ul><li>Biomarker development in liver disease, kidney dysfunction, inflammation, and systemic disorders</li><li>Mass-spectrometry method development</li><li>Computational proteomics and peptide modelling</li><li>Autoimmunity and neo-epitope analysis</li><li>Protein–peptide interaction studies</li><li>Proteolytic pathway mapping and degradomics</li></ul><h2><b>Versioning and Future Work</b></h2><p dir="ltr">This is <b>Version 1</b> of the Albumin Degradome Foundation Atlas. …"

<b>Tau Degradome Foundation Atlas</b> حسب Axel Petzold (7076261)

"…</li><li><b>Thermodynamic stability</b> is predicted for each peptide, with stable candidates labelled (<code>stable=1</code>), highlighting their suitability for biomarker assay development.…"

Critical Planck Spin Dynamics (CPSD): A Geometric Quantum Spacetime with Zero Free Parameters حسب Daniel Zunzunegui (22583093)

"…Complete Python verification code included.</p><p><br></p><p dir="ltr">This work solves the hierarchy problem, explains dark energy as geometric anisotropy, and predicts the universe's ultimate fate as "Big Silence" - eternal expansion at c/φ ≈ 0.618c.…"

Genosophus: A Dynamical-Systems Diagnostic Engine for Neural Representation Analysis حسب Alan Glanz (22109698)

"…</p><h2><b>Included Files</b></h2><h3><b>1. </b><code><strong>GenosophusV2.py</strong></code></h3><p dir="ltr">Executable Python implementation of the Genosophus Engine.…"

Synthetic Mental Health Survey Dataset حسب Shakil Hossain (22546658)

"…Data were generated using Python code to simulate realistic patterns and scoring based on psychological constructs.This dataset was to develop a machine learning model for predicting severity of multiple mental health disorders & overall Mental Health Status based on survey responses and psychological features.…"

Monte Carlo Simulation for SAPAL Framework: AI-Augmented CI/CD Reliability حسب Rohit Dhawan (22457026)

"…</p><p dir="ltr">Files included: <br>- simulation.py: Python simulation code <br>- README.md: Complete documentation and methodology <br><br>This code supports the paper "AI-Augmented Reliability in Continuous Integration and Deployment: A Conceptual Framework for Predictive, Adaptive, and Self-Correcting Pipelines".…"

<b>Antibiotics in the Global River System Arising from Human Consumption</b> حسب Heloisa Ehalt Macedo (10319300)

"…</p><p dir="ltr">The data repository includes 3 datasets:</p><p dir="ltr">1. Python code: python project repository including the structure necessary for the model to run.…"

<b>Effects of Lifestyle and GLP-1RA based Interventions on Waist Circumference: A Systematic Review and Meta-Analysis</b> حسب Samit Ghosal (22024556)

"…</li><li><b>R scripts (00–06)</b> — reproducible code for primary, sensitivity, subgroup, and meta-regression analyses, forest plots, funnel plots, ROB2 templates, and prediction intervals.…"

Accompanying data files (Melbourne, Washington DC, Singapore, and NYC-Manhattan) حسب Winston Yap (13771969)

"…Each folder contains the training and validation data, graph adjacency information, compiled reported energy consumption data for each city, and generated predictions.</p><p dir="ltr">Each zipped folder consists the following files:</p><ul><li>Graph data - City object nodes (.parquet) and COO format edges (.txt)</li><li>predictions.txt (model predictions from GraphSAGE model)</li><li>final_energy.parquet (Compiled training and validation building energy data)</li></ul><p dir="ltr">The provided files are supplementary to the code repository which provides Python notebooks stepping through the data preprocessing, GNN training, and satellite imagery download processes. …"

Leveraging explainable causal artificial intelligence to study forest gross primary productivity dynamics in China's protected areas حسب Pedro Cabral (18947566)

"…<p dir="ltr">A Python script used for modeling forest GPP in China´s Protected Areas, including mean encoding of the categorical variable climate zone (CZ), multicollinearity testing using Variance Inflation Factor (VIF), implementation of four machine learning models to predict forest GPP, XAI and causality analysis.…"

Seattle Demo Accompanying Files حسب Winston Yap (13771969)

"…<p dir="ltr">We release the data, code, and prepared city graph objects to facilitate city scale building operating energy prediction with Seattle as a case study. …"

<b>Rethinking neighbourhood boundaries for urban planning: A data-driven framework for perception-based delineation</b> حسب Shubham Pawar (22471285)

"…</p><p dir="ltr"><b>Input:</b></p><ul><li><code>raw_data/glasgow_open_built/glasgow_open_built_areas.shp</code> - Grid defining sampling points</li></ul><p dir="ltr"><b>Command:</b></p><pre><pre>python svi_module/get_svi_data.py<br></pre></pre><p dir="ltr"><b>Output:</b></p><ul><li><code>svi_module/svi_data/svi_info.csv</code> - Image metadata (IDs, coordinates)</li><li><code>svi_module/svi_data/images/</code> - Downloaded street view images</li></ul><h3>Step 2: Predict Perceptions</h3><p dir="ltr">Use pre-trained deep learning models to predict perceptual qualities (safety, beauty, liveliness, etc.) from street view images.…"

IGD-cyberbullying-detection-AI حسب Bryan James (19921044)

"…</p><h2>Requirements</h2><p dir="ltr">To run this code, you'll need the following dependencies:</p><ul><li>Python 3.x</li><li>TensorFlow</li><li>scikit-learn</li><li>pandas</li><li>numpy</li><li>matplotlib</li><li>imbalanced-learn</li></ul><p dir="ltr">You can install the required dependencies using the provided <code>requirements.txt</code> file.…"

Harmonic Shell Structures in MaDCoWS2 Clusters: Empirical Validation of Oscillatory Field Genesis (OFG) حسب Drippy Stone (21218843)

"…Analyzing 22,971 galaxy clusters from MaDCoWS2 DR2, we demonstrate: - **Harmonic shell spacings** (λ = 2π/|∇Φ·∇Θ|) in high-z clusters (z ≥ 1.5) - **Phase-locked redshift distributions** via Lomb-Scargle periodograms - **Predictive templates** for LSST void lensing (Δκ ≥ 0.5) and SPHEREx spectral harmonics Includes: - Cluster spacing histograms (`Cluster_Spacing_Histogram.csv`) - Redshift-phase coherence data (`theta_oscillation_peaks.csv`) - High-z cluster catalog (`High-Redshift_Cluster_z.csv`) - Full analysis code (Python/Jupyter) </p><p><br></p><p><br></p><p dir="ltr">Related Publications**: - Gonzalez et al. (2024) MaDCoWS2 DR2 Catalog (ApJ, 967, 123) - OFG Theoretical Framework (J.D.S. 2025, DeepSeek-verified) - **Tools Required**: Python 3.10+, NumPy, Pandas, Astropy - **Experiment Type**: Observational/Cosmological Simulation </p>…"

ncRNA.zip حسب Chongyi Jiang (20987126)

"…<h3><b>ncRNA (non-coding RNA) </b><b>predicted by</b><b> CPC2 (v 0.1) and PINC for 25 </b><b>grassland plant species.…"

MsipNet حسب Nan Song (22280815)

"…<h2><b>MsipNet</b></h2><p dir="ltr">This is a directory for storing the **MsipNet** model code and data. **MsipNet** is a multi-scale representation learning framework for predicting protein-RNA interactions.…"

<b>MSLU-100K: A multi-source land use dataset of Chinese major cities</b> حسب Yao Yao (7903457)

"…</li><li>The Manual Filtering.py-Based Multilevel Model Classification Method includes code to perform multilevel model predictions.</li></ul><h3>5.requirements.txt</h3><ul><li>Lists environment configurations and version specifications, including Python 3.7 and Pytorch 2.2.…"

Bayesian Neural Network-Based Ground Motion Model for Horizontal and V/H spectral ordinate with Epistemic Uncertainty for the European Region حسب jyothi yedulla (18319545)

"…<p dir="ltr">The Python code provides the computation of 100 predictions using the proposed BNN model for the given input parameters which includes Moment magnitude (M_w), Joyner-Boore distance (R_JB), Shear wave velocity (V_s30), focal depth (d) and focal mechanism.…"

LNP drug delivery image data حسب Philip Harrison (8899735)

"…</div><div><br></div><div><u>Python code:</u></div><div><a href="https://github.com/pharmbio/phil_LNP_modelling">https://github.com/pharmbio/phil_LNP_modelling</a><br></div><div><br></div><div><br></div><div><br></div><div><br></div><div><br></div><p></p>…"

<b>Alpha-Synuclein Degradome Foundation Atlas</b> حسب Axel Petzold (7076261)

"…</p><p dir="ltr">Whether your work involves biomarker development, precision neurology, or machine learning, this dataset provides structured, labelled inputs that are ideal for:</p><ul><li>Training supervised models to detect or predict cleavage sites</li><li>Feature extraction from protein sequences</li><li>Clustering or classification of fragment types by mutation or disease context</li><li>Integrating with omics data for multimodal prediction tasks</li></ul><p dir="ltr">Dataset Features:</p><ul><li>Annotated α-synuclein proteolytic fragments</li><li>Includes wild-type and clinically relevant variants</li><li>Tab-delimited ASCII format for compatibility with Python, R, and ML frameworks</li><li>Linked SAS and Python scripts for pipeline reproducibility and updates</li><li>Ready-to-use for computational modelling, AI training, and bioinformatics workflows</li></ul><p dir="ltr">The dataset was generated using a reproducible codes involving Python, BLAST, and SAS. …"