Fitting a feast/famine cycle to a glycolysis model. by Paul van Lent (16876977)

CSMILES: A Compact, Human-Readable SMILES Extension for Conformations by James W. Furness (22319738)

“…A two-way conversion from three-dimensional (3D) structure to CSMILES has been implemented, and the article is accompanied by a Python code which effectuates such conversions. …”

CSMILES: A Compact, Human-Readable SMILES Extension for Conformations by James W. Furness (22319738)

“…A two-way conversion from three-dimensional (3D) structure to CSMILES has been implemented, and the article is accompanied by a Python code which effectuates such conversions. …”

Scripts, data and figures underpinning 'Towards the Creation of Legible Octilinear Power Grid Diagrams Using Mixed Integer Linear Programming' by Paul Cuffe (2937081)

“…<p dir="ltr">These Python notebooks implement the techniques described in the paper "Towards the Creation of Legible Octilinear Power Grid Diagrams Using Mixed Integer Linear Programming".…”

Resolving Harvesting Errors in Institutional Repository Migration : Using Python Scripts with VS Code and LLM Integration. by satoshi hashimoto(橋本 郷史) (18851272)

“…</li></ul><h3>Result</h3><ul><li>The initial instructions yielded Python code with approx. 70-80% completion.…”

Simulation results for the phage communication circuit from Pathania <i>et al</i>. [5]. by Fabricio Cravo (21387854)

Left schematic of the XOR gate implementation [11]. by Fabricio Cravo (21387854)

Matching products with reactants for the example meta-reaction where S1 and S2 are distinct meta-species. by Fabricio Cravo (21387854)

SEPARATE Code Repository by Gyuri Kim (21424973)

Data&Codes.zip by Zer0 Star (20545655)

“…</p><p dir="ltr">To facilitate the widespread use of the proposed framework, we have implemented it as the <b><i>ESLocalIndi</i></b> open-source package in Python, making it easily accessible to geographers. …”

software code of NeoDesign by Wenqian Yu (19730101)

“…<h2>Implementation and Dependencies</h2><p dir="ltr">neoDesign was developed with python (recommend>3.9) and shell (bash) language. …”

DA-Faster-RCNN code by Seunghyeon Wang (16500132)

“…The implementation is written in Python using PyTorch and Detectron2.…”

Reproducible Code and Data for figures by Bonyad Ahmadi (20750327)

“…</i></p><p dir="ltr">It contains:</p><p dir="ltr">✅ <b>Python Code</b> – Scripts used for data preprocessing, and visualization.…”

Simulation Code and Raw Data by Melih Özkurt (22278520)

“…<p dir="ltr">Reproducible code (Python) implementing a symmetrized split-step Fourier method (SSFM), with configuration files for all scans. …”

Introduction to the iModulonMiner using public <i>B</i>. <i>subtilis</i> RNA-seq data as a case study. by Anand V. Sastry (6619310)

MCCN Case Study 3 - Select optimal survey locality by Donald Hobern (21435904)

“…</p><p dir="ltr">This is a simple implementation that uses four environmental attributes imported for all Australia (or a subset like NSW) at a moderate grid scale:</p><ol><li>Digital soil maps for key soil properties over New South Wales, version 2.0 - SEED - see <a href="https://esoil.io/TERNLandscapes/Public/Pages/SLGA/ProductDetails-SoilAttributes.html" target="_blank">https://esoil.io/TERNLandscapes/Public/Pages/SLGA/ProductDetails-SoilAttributes.html</a></li><li>ANUCLIM Annual Mean Rainfall raster layer - SEED - see <a href="https://datasets.seed.nsw.gov.au/dataset/anuclim-annual-mean-rainfall-raster-layer" target="_blank">https://datasets.seed.nsw.gov.au/dataset/anuclim-annual-mean-rainfall-raster-layer</a></li><li>ANUCLIM Annual Mean Temperature raster layer - SEED - see <a href="https://datasets.seed.nsw.gov.au/dataset/anuclim-annual-mean-temperature-raster-layer" target="_blank">https://datasets.seed.nsw.gov.au/dataset/anuclim-annual-mean-temperature-raster-layer</a></li></ol><h4><b>Dependencies</b></h4><ul><li>This notebook requires Python 3.10 or higher</li><li>Install relevant Python libraries with: <b>pip install mccn-engine rocrate</b></li><li>Installing mccn-engine will install other dependencies</li></ul><h4><b>Overview</b></h4><ol><li>Generate STAC metadata for layers from predefined configuratiion</li><li>Load data cube and exclude nodata values</li><li>Scale all variables to a 0.0-1.0 range</li><li>Select four layers for comparison (soil organic carbon 0-30 cm, soil pH 0-30 cm, mean annual rainfall, mean annual temperature)</li><li>Select 10 random points within NSW</li><li>Generate 10 new layers representing standardised environmental distance between one of the selected points and all other points in NSW</li><li>For every point in NSW, find the lowest environmental distance to any of the selected points</li><li>Select the point in NSW that has the highest value for the lowest environmental distance to any selected point - this is the most different point</li><li>Clean up and save results to RO-Crate</li></ol><p><br></p>…”

The format of the electrode csv file by Joseph James Tharayil (21416715)

“…To enable efficient calculation of extracellular signals from large neural network simulations, we have developed <i>BlueRecording</i>, a pipeline consisting of standalone Python code, along with extensions to the Neurodamus simulation control application, the CoreNEURON computation engine, and the SONATA data format, to permit online calculation of such signals. …”

The format of the simulation reports by Joseph James Tharayil (21416715)

“…To enable efficient calculation of extracellular signals from large neural network simulations, we have developed <i>BlueRecording</i>, a pipeline consisting of standalone Python code, along with extensions to the Neurodamus simulation control application, the CoreNEURON computation engine, and the SONATA data format, to permit online calculation of such signals. …”

Comparison of BlueRecording with existing tools by Joseph James Tharayil (21416715)

“…To enable efficient calculation of extracellular signals from large neural network simulations, we have developed <i>BlueRecording</i>, a pipeline consisting of standalone Python code, along with extensions to the Neurodamus simulation control application, the CoreNEURON computation engine, and the SONATA data format, to permit online calculation of such signals. …”

The format of the weights file by Joseph James Tharayil (21416715)

“…To enable efficient calculation of extracellular signals from large neural network simulations, we have developed <i>BlueRecording</i>, a pipeline consisting of standalone Python code, along with extensions to the Neurodamus simulation control application, the CoreNEURON computation engine, and the SONATA data format, to permit online calculation of such signals. …”