Comparison data 1 for <i>Lamprologus ocellatus</i>. حسب Nicolai Kraus (19949667)

"…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …"

Comparison data 2 for <i>Lamprologus ocellatus</i>. حسب Nicolai Kraus (19949667)

"…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …"

Comparison data 5 for <i>Lamprologus ocellatus</i>. حسب Nicolai Kraus (19949667)

"…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …"

Comparison data 6 for <i>Lamprologus ocellatus</i>. حسب Nicolai Kraus (19949667)

"…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …"

Reaction Alignment of the Tricarboxylic Acid (TCA) Cycle Network. حسب Adel Heydarabadipour (22290905)

Workflow of segmentation model creation and application. حسب Vincent Hickl (16947429)

Performance Benchmark: SBMLNetwork vs. SBMLDiagrams Auto-layout. حسب Adel Heydarabadipour (22290905)

"…<p>Log–log plot of median wall-clock time for SBMLNetwork’s C++-based auto-layout engine (blue circles, solid fit) and SBMLDiagrams’ implementation of the pure-Python NetworkX spring_layout algorithm (red squares, dashed fit), applied to synthetic SBML models containing 20–2,000 species, with a fixed 4:1 species-to-reaction ratio. …"

Spherical Texture method design. حسب 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. …"

A Hybrid Ensemble-Based Parallel Learning Framework for Multi-Omics Data Integration and Cancer Subtype Classification حسب Mohammed Nasser Al-Andoli (21431681)

"…<p dir="ltr">The code supports replication of results on TCGA Pan-cancer and BRCA datasets and includes data preprocessing, model training, and evaluation scripts:<br>Python scripts for data preprocessing and integration</p><ul><li>Autoencoder implementation for multimodal feature learning</li><li>Hybrid ensemble training code (DL/ML models and meta-learner)</li><li>PSO and backpropagation hybrid optimization code</li><li>Parallel execution scripts</li><li>Instructions for replicating results on TCGA Pan-cancer and BRCA datasets</li></ul><p></p>…"

Deep Learning-Based Visual Enhancement and Real-Time Underground-Mine Water Inflow Detection حسب 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".…"

Core-Based Smart Sampling Framework: A Theoretical and Experimental Study on Randomized Partitioning for SAT Problems حسب DURGHAM QARALLEH (21904172)

"…We provide theoretical guarantees on complexity reduction and probabilistic completeness, apply the method to SAT instances, and evaluate its performance using experimental Python implementations. The results show that smart sampling drastically reduces the effective complexity of SAT problems and offers new insights into the structure of NP-complete problems.…"

Linking Thermal Conductivity to Equations of State Using the Residual Entropy Scaling Theory حسب Zhuo Li (165589)

"…To use our model easily, a software package written in Python is provided in the Supporting Information.…"

Reinforcement Learning based traffic steering inOpen Radio Access Network (ORAN)- oran-ts GitHub Repository حسب Aaradhy Sharma (21503465)

"…It features a modular Python framework implementing various RL agents (Q-Learning, SARSA, N-Step SARSA, DQN) and a traditional baseline evaluated in a realistic cellular network environment. …"

Single Cell DNA methylation data for Human Brain altas (MajorType+Region CG allc files) حسب 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>…"

Supplementary file 1_ParaDeep: sequence-based deep learning for residue-level paratope prediction using chain-aware BiLSTM-CNN models.docx حسب Piyachat Udomwong (22563212)

"…Its efficiency and scalability make it well-suited for early-stage antibody discovery, repertoire profiling, and therapeutic design, particularly in the absence of structural data. The implementation is freely available at https://github.com/PiyachatU/ParaDeep, with Python (PyTorch) code and a Google Colab interface for ease of use.…"

Table 3_Novel deep learning-based prediction of HER2 expression in breast cancer using multimodal MRI, nomogram, and decision curve analysis.docx حسب Shi Qiu (425335)

"…Statistical analyses were conducted using Python and R, with significance set at p < 0.05.</p>Results<p>In this study, we developed an integrated predictive model for HER2 status in breast cancer by combining deep learning-based MRI features and clinical data. …"

Table 2_Novel deep learning-based prediction of HER2 expression in breast cancer using multimodal MRI, nomogram, and decision curve analysis.docx حسب Shi Qiu (425335)

"…Statistical analyses were conducted using Python and R, with significance set at p < 0.05.</p>Results<p>In this study, we developed an integrated predictive model for HER2 status in breast cancer by combining deep learning-based MRI features and clinical data. …"

Table 1_Novel deep learning-based prediction of HER2 expression in breast cancer using multimodal MRI, nomogram, and decision curve analysis.docx حسب Shi Qiu (425335)

"…Statistical analyses were conducted using Python and R, with significance set at p < 0.05.</p>Results<p>In this study, we developed an integrated predictive model for HER2 status in breast cancer by combining deep learning-based MRI features and clinical data. …"

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

Data Sheet 1_Novel deep learning-based prediction of HER2 expression in breast cancer using multimodal MRI, nomogram, and decision curve analysis.docx حسب Shi Qiu (425335)

"…Statistical analyses were conducted using Python and R, with significance set at p < 0.05.</p>Results<p>In this study, we developed an integrated predictive model for HER2 status in breast cancer by combining deep learning-based MRI features and clinical data. …"