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

Apple point cloud generated by python script. by Xiaoyang Liu (1815211)

RNA Velocity model simulation results. (A) Simulation results for RNA Velocity model without delay ( samples). The simulation is composed of an up-regulation phase (both production... by Ziyan Jin (21021976)

BaNDyT: Bayesian Network Modeling of Molecular Dynamics Trajectories by Elizaveta Mukhaleva (20602550)

“…We describe here the software’s uses, the methods associated with it, and a comprehensive Python interface to the underlying generalist BNM code. …”

BaNDyT: Bayesian Network Modeling of Molecular Dynamics Trajectories by Elizaveta Mukhaleva (20602550)

“…We describe here the software’s uses, the methods associated with it, and a comprehensive Python interface to the underlying generalist BNM code. …”

BaNDyT: Bayesian Network Modeling of Molecular Dynamics Trajectories by Elizaveta Mukhaleva (20602550)

“…We describe here the software’s uses, the methods associated with it, and a comprehensive Python interface to the underlying generalist BNM code. …”

A comparison between the static Python-based visualizations of the p65 activity in activated fibroblasts and the dynamic, HTML-based visualizations that use these same reduction me... by Hector Torres (11708207)

“…<p><b>(a)</b> UMAP, t-SNE, PCA, and Diffmap were first generated using the Python libraries Scikit-learn, UMAP, and PyDiffmap within Jupyter to generate static graphs as a starting point. …”

BlueRecording simulates hippocampal LFP. by Joseph James Tharayil (21416715)

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

“…To our knowledge, this is the first application of this generalized (i.e., non-dipolar) reciprocity-based approach to simulate EEG recordings. …”

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

“…To our knowledge, this is the first application of this generalized (i.e., non-dipolar) reciprocity-based approach to simulate EEG recordings. …”

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

“…To our knowledge, this is the first application of this generalized (i.e., non-dipolar) reciprocity-based approach to simulate EEG recordings. …”

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

“…To our knowledge, this is the first application of this generalized (i.e., non-dipolar) reciprocity-based approach to simulate EEG recordings. …”

Supporting data for "Interpreting complex ecological patterns and processes across differentscales using Artificial Intelligence" by Yifei Gu (9507104)

“…</p><p dir="ltr">Firstly, a Python package HSC3D, was developed to quantify habitat structural complexity (HSC) at the community level. …”

Efficient, Hierarchical, and Object-Oriented Electronic Structure Interfaces for Direct Nonadiabatic Dynamics Simulations by Sascha Mausenberger (22225772)

“…We present a novel, flexible framework for electronic structure interfaces designed for nonadiabatic dynamics simulations, implemented in Python 3 using concepts of object-oriented programming. …”

The codes and data for "A Graph Convolutional Neural Network-based Method for Predicting Computational Intensity of Geocomputation" by FirstName LastName (20554465)

The codes and data for "A Graph Convolutional Neural Network-based Method for Predicting Computational Intensity of Geocomputation" by FirstName LastName (20554465)

Spherical Texture method design. by Oane Gros (20636735)

“…<b>H)</b> The <i>Spherical Texture</i> extraction is implemented as a Python package and it is directly available in <i>ilastik</i>, allowing for its adoption into the Object Classification workflow. …”

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. …”

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. …”

Image 1_Differential diagnosis of pneumoconiosis mass shadows and peripheral lung cancer using CT radiomics and the AdaBoost machine learning model.tif by Xiaobing Li (291454)

“…LR, SVM, and AdaBoost algorithms were implemented using Python to build the models. In the training set, the accuracies of the LR, SVM, and AdaBoost models were 79.4, 84.0, and 80.9%, respectively; the sensitivities were 74.1, 74.1, and 81.0%, respectively; the specificities were 83.6, 91.8, and 80.8%, respectively; and the AUC values were 0.837, 0.886, and 0.900, respectively. …”