Overview of the SBML models used in this study. The collection of models was retrieved from Biomodels [43] and a previously reported collection of SBML benchmark models [11]. The n... by Paul van Lent (16876977)

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Exploring the integration of metaverse technologies in engineering education through the SAMR model by Snezhana Dineva (22444471)

“…The final deliverable is a plan for phased integration of metaverse learning into a Python programming course following this model, building on existing best practices.…”

Jaxkineticmodel allows for hybridizing kinetic models with neural networks. by Paul van Lent (16876977)

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Analysis of convergence properties for a collection of SBML models. by Paul van Lent (16876977)

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EFGs: A Complete and Accurate Implementation of Ertl’s Functional Group Detection Algorithm in RDKit by Gonzalo Colmenarejo (650249)

“…In this paper, a new RDKit/Python implementation of the algorithm is described, that is both accurate and complete. …”

2D Orthogonal Planes Split: <b>Python</b> and <b>MATLAB</b> code | <b>Source Images</b> for Figures by Nektarios Valous (20715650)

“…The output files generated by the code include results from both Python and MATLAB implementations; these output images are provided as validation, demonstrating that both implementations produce matching results.…”

Python file of the computational framework. by Benoit Haut (9753029)

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

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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. …”

Cost functions implemented in Neuroptimus. by Máté Mohácsi (20469514)

“…To address these issues, we developed a generic platform (called Neuroptimus) that allows users to set up neural parameter optimization tasks via a graphical interface, and to solve these tasks using a wide selection of state-of-the-art parameter search methods implemented by five different Python packages. Neuroptimus also offers several features to support more advanced usage, including the ability to run most algorithms in parallel, which allows it to take advantage of high-performance computing architectures. …”

Illustration of the text transformation process before and after synonym replacement: The process begins with a sample initial text segment (Sample text before synonym replacement’... by Enock Niyonkuru (21246879)

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Schematic of the approach: This schematic illustrates the entire workflow of the project. by Enock Niyonkuru (21246879)

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Text Transformation Pipeline: An example of the multi-stage text transformation pipeline applied to a sample abstract (PMID: 30609739). by Enock Niyonkuru (21246879)

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Comparative analysis of WordNet replacement impact on data distribution. by Enock Niyonkuru (21246879)

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Comparison of window size for embedding with Wordnet synonym replacement (WN) and without (PM). While Table 1 compared the effects of different values of using a window size of 10,... by Enock Niyonkuru (21246879)

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Non-biomedical word replacement algorithm: This algorithm outlines the process for replacing non-biomedical words in a corpus using WordNet. by Enock Niyonkuru (21246879)

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Comparison of mean interconcept distance for embedding with WordNet synonym replacement (WN) and without (PM). The initial number of unique concepts in the total corpus was 3,018,9... by Enock Niyonkuru (21246879)

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