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

“…</p>Conclusions<p>This study demonstrates that integrating deep learning with multi-sequence breast MRI and clinical data provides a highly effective and reliable tool for predicting HER2 expression in breast cancer. …”

Oka et al., Supplementary Data for "Development of a battery emulator using deep learning model to predict the charge–discharge voltage profile of lithium-ion batteries" by Kanato Oka (20132185)

“…For a single file, test data is read, and the prediction plot is output. To use this Python script, you need to modify the "CFG (config)" and "Convenient" sections within the script.…”

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

“…The implementation is freely available at https://github.com/PiyachatU/ParaDeep, with Python (PyTorch) code and a Google Colab interface for ease of use.…”

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

“…</p>Conclusions<p>This study demonstrates that integrating deep learning with multi-sequence breast MRI and clinical data provides a highly effective and reliable tool for predicting HER2 expression in breast cancer. …”

Discovery of a Latent Entropy-Based Physiologic State Variable Governing Multisystem Instability in Critical Illness by Jordan Rabbani (22800074)

Data Sheet 1_Machine learning-driven prediction of intratumoral tertiary lymphoid structures in hepatocellular carcinoma using contrast-enhanced CT imaging and integrated clinical... by Jun Wu (4002)

“…Using Python software, we extracted radiomic features from preoperative CT images (arterial and portal venous phases). …”

Tipping points of marine phytoplankton to multiple environmental stressors by Zhan Ban (11627098)

Data for: An effective methodology to quantify cooling demand in the UK housing stock by Lloyd Corcoran (19094369)

Template customisation process. by John J. L. Jacobs (20536002)

Global Aridity Index and Potential Evapotranspiration (ET0) Database: Version 3.1 by Robert Zomer (12796235)

A model of neural population dynamics for flexible sensorimotor control by Hari Kalidindi (17123467)

Machine Learning-Driven Discovery and Database of Cyanobacteria Bioactive Compounds: A Resource for Therapeutics and Bioremediation by Renato Soares (20348202)

“…A Python programming protocol obtained 3431 cyanobacteria bioactive compounds, 373 unique protein targets, and 3027 molecular descriptors. …”

Methodological Approach Based on Structural Parameters, Vibrational Frequencies, and MMFF94 Bond Charge Increments for Platinum-Based Compounds by Gloria Castañeda-Valencia (20758502)

“…The developed bci optimization tool, based on MMFF94, was implemented using a Python code made available at https://github.com/molmodcs/bci_solver. …”

Tracking when the number of individuals in the video frame changes. by Hirotsugu Azechi (20700528)

“…The removal of unnecessary keypoint data is achieved through a Python code that allows specified ranges of tracking data obtained from DeepLabCut to be rewritten as NaN (no data) (<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.3003002#pbio.3003002.s019" target="_blank">S1 Protocol</a> and <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.3003002#pbio.3003002.s010" target="_blank">S10C Fig</a>). …”

RNACOREX package workflow. by Aitor Oviedo-Madrid (22553399)

“…However, identifying reliable sets of such interactions associated with specific diseases remains challenging, partly due to the high rate of false positives and the lack of user-friendly tools developed for this purpose. In this work, we introduce a new Python package called RNACOREX (RNA CORegulatory network EXplorer and classifier). …”

Performance. by Aitor Oviedo-Madrid (22553399)

“…However, identifying reliable sets of such interactions associated with specific diseases remains challenging, partly due to the high rate of false positives and the lack of user-friendly tools developed for this purpose. In this work, we introduce a new Python package called RNACOREX (RNA CORegulatory network EXplorer and classifier). …”

Void-Center Galaxies and the Gravity of Probability Framework: Pre-DESI Consistency with VGS 12 and NGC 6789 by Jordan Waters (21620558)

“…<br><br><br><b>ORCID ID: https://orcid.org/0009-0009-0793-8089</b><br></p><p dir="ltr"><b>Code Availability:</b></p><p dir="ltr"><b>All Python tools used for GoP simulations and predictions are available at:</b></p><p dir="ltr"><b>https://github.com/Jwaters290/GoP-Probabilistic-Curvature</b><br><br>The Gravity of Probability framework is implemented in this public Python codebase that reproduces all published GoP predictions from preexisting DESI data, using a single fixed set of global parameters. …”

MsipNet by Nan Song (22280815)

“…<b>RNAfold-structures</b>: The secondary structure information predicted using the RNAfold tool.</h4><h4>d). <b>RNAshapes-structures</b>: The secondary structure information predicted using the RNAshapes tool.…”

<b>Tau Degradome Foundation Atlas</b> by Axel Petzold (7076261)

“…</li><li><b>Compression format:</b> Datasets are distributed in <code>.tar.gz</code> format and can be extracted with:</li></ul><pre></pre><pre><code>tar -xvzf FILENAME.tar.gz</code><br><br></pre><p dir="ltr"><b>Reproducibility and Methods</b><br>All datasets can be fully regenerated using open-source software tools, including <b>Python</b> and <b>SAS</b>. …”

The data of the paper "Remote spectral detection of canopy functional strategies varying within and across forest types". by Fengqi Wu (20149158)

“…Canopy_2024_PLSR_ST_canopy_run_refit.py</p><p dir="ltr">This is the python code used for PLSR modeling.</p><p dir="ltr"><br></p><p dir="ltr">3. python_code_get_model_details.zip</p><p dir="ltr">This is the python code to get model performance, coefficients, VIPs, and so on.…”