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

“…</li><li>The Manual Filtering.py-Based Multilevel Model Classification Method includes code to perform multilevel model predictions.…”

Scripts_scParadise_article by Vadim Chechekhin (20569496)

“…ScAdam outperforms existing annotation methods by providing enhanced consistency and offers a model hub of over 30 pre-trained models. ScEve enables accurate imputation of cell surface protein markers, facilitating cell type annotation and in-depth multi-omic analyses in different tissues and species. …”

Multi-Task Learning in Analyzing the Working capacity of MOFs by Junhui Kou (20327073)

“…</p><ul><li><b>CIF files</b>: CIF files for 252,352 MOFs;</li><li><b>Geometric descriptors</b>: 14 geometric descriptors;</li><li><b>Chemical descriptors</b>: 176 chemical descriptors;</li><li><b>Methane_v, Methane_g</b>: Volumetric and gravimetric working capacities for methane adsorption, including methane adsorption data under six pressures across three application scenarios (landfill gas treatment, methane purification, and methane storage);</li><li><b>MTL4MOFsWC</b>: Python code for training the MTL models to predict the working capacity of methane adsorption in MOFs;</li><li><b>best_model_v_full, best_model_v_sim, best_model_g_full, best_model_g_sim</b>: Pre-trained MTL models.…”

MsipNet by 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.…”

DCPR_V1.0 by xiao han (21405770)

“…</p><p dir="ltr"><b>DCPR_codes</b>: Source code for DCPR model.</p><p dir="ltr"><b>Visualization</b>: Scripts for data visualization, including circadian curves (cosine model fitting), sample plots (predicted and real time), model performance (CDF curves, and accuracy plots).…”

<b>Alpha-Synuclein Degradome Foundation Atlas</b> by 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. …”

<b>Effects of Lifestyle and GLP-1RA based Interventions on Waist Circumference: A Systematic Review and Meta-Analysis</b> by 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.</li><li><b>Python script (05_correlation_python.py)</b> — scatter plot of WC vs. …”

Machine Learning-Driven Discovery and Database of Cyanobacteria Bioactive Compounds: A Resource for Therapeutics and Bioremediation by Renato Soares (20348202)

“…In this study, a searchable, updated, curated, and downloadable database of cyanobacteria bioactive compounds was designed, along with a machine-learning model to predict the compounds’ targets of newly discovered molecules. …”

Leveraging explainable causal artificial intelligence to study forest gross primary productivity dynamics in China's protected areas by 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.…”

Fast, FAIR, and Scalable: Managing Big Data in HPC with Zarr by Alfonso Ladino (21447002)

“…Nesbitt1, Deepack Cheerian2 </p><ol><li>University of Illinois at Urbana-Champaign </li></ol><ol><li>Earthmover PBC </li></ol><p dir="ltr">The explosive growth of high-resolution, multidimensional data — from radar and satellite imagery to weather prediction, climate modeling, MRI and microscopy in medicine and biology, CFD simulations in engineering, and large-scale machine learning datasets — is pushing the limits of traditional data storage and processing methods. …”

<b>Exploring Multiverse Dynamics Through the HEX Formula: Applications in Quantum Entanglement, Dark Matter, and Wormhole Stability</b>(Simulations Resources) by Hector Ortiz (18802150)

“…<p dir="ltr">This repository provides Python simulations designed to illustrate the HEX formula’s predictions for multiverse interactions. …”

Image 1_An explainable analysis of depression status and influencing factors among nursing students.png by Yingying Li (50341)

“…According to the random forest model, the order of depression predicted by this study from high to low is Sleep Condition, Social anxiety, Mother's Educational Level, Sexual Orientation, Smoking, and Household composition.…”

Critical Planck Spin Dynamics (CPSD): A Geometric Quantum Spacetime with Zero Free Parameters by 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.…”

mdata_pbmc.h5mu by Vadim Chechekhin (20569496)

“…</p><p dir="ltr">scNoah facilitates the evaluation of novel models and methods for automated cell type annotation and modality prediction in scRNA-seq analysis.…”

Galaxy Zoo: Cosmic Dawn -- morphological classifications for over 41,000 galaxies in the Euclid Deep Field North from the Hawaii Two-0 Cosmic Dawn survey by James Pearson (554629)

“…The data consists of classifications made by volunteers through the Galaxy Zoo project on the Zooniverse citizen science platform, as well as predicted classifications made by a deep learning model, Zoobot. …”

HMRLBA_V1.0 by Zhenyu Huang (20153082)

“…<h2><b>HMRLBA</b></h2><p dir="ltr">This is a repository to deposit the data and code for HMRLBA model. HMRLBA is a hierarchical multi-scale representation learning model for predicting protein-ligand binding affinity.…”

Murakami et al. Supplemental Data for "Microstructural Analysis of Li-Ion Conductors with Deep Learning and SEM Images" by Kento Murakami (21260244)

“…</p><h2><b>SEM_images.zip</b>: </h2><p dir="ltr">These files consists of SEM images and numerical datasets (descriptors and objective variables) of composition, sintering temperature, and ionic conductivities for 52 samples (1-3 SEM images are included per 1 sample, total 130 images)</p><h2><b>python_codes.zip</b>: </h2><p dir="ltr">Python codes for four convolutional neural network (CNN) models used to investigate the relationship between these image data and ionic conductivity are provided.…”

<b>Rethinking neighbourhood boundaries for urban planning: A data-driven framework for perception-based delineation</b> by 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.…”

Geometric Mechanics and Stokes’ Theorem in Robotic Locomotion by Umar Tabbsum (22058780)

“…<p dir="ltr">This research develops a rigorous mathematical framework for analyzing and predicting robotic locomotion using the principles of geometric mechanics. …”

Ambient Air Pollutant Dynamics (2010–2025) and the Exceptional Winter 2016–17 Pollution Episode: Implications for a Uranium/Arsenic Exposure Event by Thomas Clemens Carmine (19756929)

“…Includes imputation statistics, data dictionary, and the Python imputation code (Imputation_Air_Pollutants_NABEL.py). …”