<b>Testing AI Applications Under Nondeterminism, Drift, and Resource Constraints</b> by Nariman Mani (21380459)

“…<ul><li>A <b>Python repo</b> with minimal implementations of all five layers<br>(<b>COL</b>, <b>SCL</b>, <b>CDM</b>, <b>RPE</b>, <b>RAS</b>) plus an <b>orchestrator</b> and utilities.…”

Concurrent spin squeezing and field tracking with machine learning by Junlei Duan (18393642)

“…<p dir="ltr">The dataset contains:</p><ol><li>Steady_squeezing.zip <b>a)</b> data for steady squeezing data and characteraztion <b>b)</b> data for pulse RF magnetormeter</li><li>Tracking1.zip <b>a)</b> data of OU process for Deep learning <b>b)</b> data of OU-jump process for Deep learning</li><li>Tracking2.zip <b>a)</b> data of white noise process in backaction experiment <b>b) </b>data of white noise process in rearrange experiment</li><li>Code <b>a)</b> Randomly signal generating code <b>b)</b> Deep learning codec.data pre-processing code</li></ol><p dir="ltr">The network is implemented using the torch 1.13.1 framework and CUDA 11.6 on Python 3.8.8. …”

Single Cell DNA methylation data for Human Brain altas (MajorType+Region CG allc files) by Wubin Ding (11823941)

“…</p><p dir="ltr">PMID: 37824674</p><p><br></p><h2>How to download</h2><p dir="ltr">To quickly download the whole folder, Python package <a href="https://github.com/DingWB/pyfigshare" rel="noreferrer" target="_blank">pyfigshare</a> can be implemented. please refer to pyfigshare documentation: <a href="https://github.com/DingWB/pyfigshare" rel="noreferrer" target="_blank">https://github.com/DingWB/pyfigshare</a></p><p dir="ltr">for example: <code>figshare download 28424780 -o downlnoaded_data</code></p>…”

Copy number contingency table. by Yang Wu (66682)

“…Our methods are implemented in Python and are freely available from GitHub (<a href="https://github.com/queryang/PASO" target="_blank">https://github.com/queryang/PASO</a>).…”

Gene mutation contingency table. by Yang Wu (66682)

“…Our methods are implemented in Python and are freely available from GitHub (<a href="https://github.com/queryang/PASO" target="_blank">https://github.com/queryang/PASO</a>).…”

Resistant & sensitive cell line Info on AZD5991. by Yang Wu (66682)

“…Our methods are implemented in Python and are freely available from GitHub (<a href="https://github.com/queryang/PASO" target="_blank">https://github.com/queryang/PASO</a>).…”

Resistant & sensitive drug info on COLO800. by Yang Wu (66682)

“…Our methods are implemented in Python and are freely available from GitHub (<a href="https://github.com/queryang/PASO" target="_blank">https://github.com/queryang/PASO</a>).…”

3D PD-Controlled Nanorobot Swarm Simulation for Targeted Cancer and BBB Therapy by Umar Tabbsum (22058780)

“…Cancer-targeting nanorobots converge rapidly, while BBB-targeting nanorobots follow more complex paths due to navigation constraints.</p><p dir="ltr">Implemented in Python (NumPy, Matplotlib, 3D visualization), the framework is fully annotated and reproducible. …”

Concurrent spin squeezing and field tracking with machine learning by Junlei Duan (18393642)

“…Randomly signal generating codeb.Deep learning codec.data pre-processing code The network is implemented using the torch 1.13.1 framework and CUDA 11.6 on Python 3.8.8. …”

MSc Personalised Medicine at Ulster University by Steven Watterson (100045)

“…</b> Introducing computational approaches to studying genes, proteins or metabolites, this module teaches Python coding, data analysis and how to work with the databases that support data analysis.…”

<b>Data Availability</b> by Bonyad Ahmadi (20750327)

“…</p><p dir="ltr">Reproducibility Resources:</p><p dir="ltr">Python scripts for reproducing figures, preprocessing data, and training machine learning models (SVM, MLP, XGB, BRR, KRR).…”

<b>Data Availability</b> by Bonyad Ahmadi (20750327)

“…</p><p dir="ltr">Reproducibility Resources:</p><p dir="ltr">Python scripts for reproducing figures, preprocessing data, and training machine learning models (SVM, MLP, XGB, BRR, KRR).…”

Gene Editing using Transformer Architecture by Rishabh Garg (5261744)

“…., the H-Bot sequence), it facilitates on-screen gene editing, enabling targeted mutations or the insertion of desired genes. Implementation requires Python and deep learning frameworks like TensorFlow or PyTorch, with optional use of Biopython for genetic sequence handling. …”

Deep Learning-Based Visual Enhancement and Real-Time Underground-Mine Water Inflow Detection by Huichao Yin (14589020)

“…<p dir="ltr">Python image preprocessing and model implementation for research of "Deep Learning-Based Visual Enhancement and Real-Time Underground-Mine Water Inflow Detection".…”

Research Database by Ana Paula Fermiano (22439479)

“…</p><p dir="ltr">Statistical analysis was conducted through <b>multiple regression models</b> implemented in <b>Jamovi</b>, supported by Geographic Information System (GIS) tools to visualize spatial patterns. …”

Comprehensive Fluid and Gravitational Dynamics Script for General Symbolic Navier-Stokes Calculations and Validation by Stylianos Touloumidis (19938747)

“…It provides a flexible foundation on which theoretical assumptions can be validated, and practical calculations performed. Implemented in Python with symbolic calculations, the script facilitates in-depth analysis of complex flow patterns and makes advanced mathematical computations more accessible. …”

Genomic Surveillance of Pemivibart (VYD2311) Escape-Associated Mutations in SARS-CoV-2: December 2025 BioSamples (n=2) by Tahir Bhatti (20961974)

“…Full source code and version details are available upon request.…”

Supplementary Data: Biodiversity and Energy System Planning - Queensland 2025 by Andrew Rogers (17623239)

“…</p><h2>Software and Spatial Resolution</h2><p dir="ltr">The VRE siting model is implemented using Python and relies heavily on ArcGIS for comprehensive spatial data handling and analysis.…”

Supplementary Material by Aris Shahbazian (22464325)

“…The supplementary material includes the full Python-based implementation of the AI-driven optimization framework described in the manuscript. …”

NanoDB: Research Activity Data Management System by Lorenci Gjurgjaj (19702207)

“…Cross-Platform Compatibility: Works on Windows, macOS, and Linux. In a Python environment or as an executable. Ease of Implementation: Using the flexibility of the Python framework all the data setup and algorithm can me modified and new functions can be easily added. …”