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.…”

Bacterial persistence modulates the speed, magnitude and onset of antibiotic resistance evolution by Giorgio Boccarella (22810952)

“…</p><p dir="ltr">complete_data.xlsx</p><p dir="ltr">A single Excel file containing 18 sheets with data from all figures:</p><p dir="ltr">Sheet names and descriptions:</p><ul><li>Fig_1: Probability of emergence contour data</li><li>Fig_2_b: MIC evolution simulation data</li><li>Fig_2_c: Speed of resistance evolution data</li><li>Fig_2_d: Time to resistance data</li><li>Fig_2_a_d_time_series_sim7: Simulation time series data (representative simulation, low persistence)</li><li>Fig_2_a_d_MIC_values_sim7: MIC values from simulation (representative simulation, low persistence)</li><li>Fig_2_a_p_time_series_sim5: Simulation time series data (representative simulation, high persistence)</li><li>Fig_2_a_p_MIC_values_sim5: MIC values from simulation (representative simulation, high persistence)</li><li>Fig_3_a-b: Distribution plot simulation data</li><li>Fig_3_a-b_empirical: Distribution plot empirical data</li><li>Fig_4_a: Mutation count simulation data</li><li>Fig_4_b: Mutation count empirical data</li><li>Fig_4_c: Mutation functional data</li><li>Fig_5_a-b: Large-scale simulation results (heatmap data)</li><li>Fig_5_c_mic: MIC heatmap empirical data</li><li>Fig_5_c_extinction: Extinction heatmap empirical data</li><li>Fig_6: Population size analysis simulation data</li><li>S1_figure: Supplementary experimental survival data</li></ul><p dir="ltr">Column naming convention</p><p dir="ltr">All sheets use consistent, tidy column names.…”

Performance Benchmark: SBMLNetwork vs. SBMLDiagrams Auto-layout. by 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. …”

Intersection and distinction of essential compounds and targets from 5 primary sources. by Gyaltsen Dakpa (21439920)

“…<b>(B)</b> UniProt and SwissTarget Prediction-predicted target proteins and 658 actives are intersected using the Jvenn Python to plot the intersection of targets in which Purple represents <i>R. officinalis</i>, Green indicates S. officinalis, Orange represents <b><i>T.…”

<b>Dataset for manuscript: </b><b>Phylogenetic and genomic insights into the evolution of terpenoid biosynthesis genes in diverse plant lineages</b> by Puguang Zhao (19023065)

“…</p><p dir="ltr"> Generates a scatter plot with a linear regression line and saves it as 'Correlation_Plot.pdf' (Figure 5D).…”

Folder with all data and algorithms by Jorge Servert Lerdo de Tejada (22290001)

“…<p dir="ltr">Spatially Offset Raman Spectroscopy (SORS) has emerged as a potential tool for non-invasive biomedical diagnostics, enabling molecularly specific probing of subsurface tissues. …”

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. …”

Table 3_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. …”

Table 2_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. …”

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. …”

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. …”

The global dryland lake storage (GDLS) dataset by Gang Zhao (18368925)

“…</b><b>ipynb</b><br>A Python example to show the location of a given lake and to plot monthly time series of area/elevation/storage for this lake.…”

Comprehensive Fluid and Gravitational Dynamics Script for General Symbolic Navier-Stokes Calculations and Validation by Stylianos Touloumidis (19938747)

“…It provides a flexible foundation on which theoretical assumptions can be validated, and practical calculations performed. Implemented in Python with symbolic calculations, the script facilitates in-depth analysis of complex flow patterns and makes advanced mathematical computations more accessible. …”

World Heritage documents reveal persistent gaps between climate awareness and local action by Yang Chen (20756166)

“…The analysis section includes a GLM model implemented in R, along with evaluation tools such as correlation heatmaps, ICC agreement analysis, and MCC-based binary classification assessment. …”

Interleg coordination in 103 adult <i>Hypsibius exemplaris</i> individuals. by Emma M. Anderson (19697573)

“…D. Probability density plot of ϕ_C vs. ϕ_I for second and third pair legs, n = 4414 strides. …”

Advancing Solar Magnetic Field Modeling by Carlos António (21257432)

“…<br><br>We developed a significantly faster Python code built upon a functional optimization framework previously proposed and implemented by our team. …”

Knowledge Graph validation using SHACL Shapes by Ángel Iglesias Préstamo (19745767)

“…Leveraging Rust’s performance and safety features, rudof provides efficient validation tools and Python bindings for integration with data science workflows. …”

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

“…The diagram illustrates changes across different experimental conditions, with plots indicating the frequency for each keypoint and bars representing each ID pair. …”

Sonification of Warming Stripes by Christopher Harrison (9448751)

“…A zip file containing all of the scripts (in the form of Python Jupyter notebooks) that were used to produce the sonification, and the plots for the explanation article (Sonification Warming Stripes.pdf). …”

Genomic Surveillance of Pemivibart (VYD2311) Escape-Associated Mutations in SARS-CoV-2: December 2025 BioSamples (n=2) by Tahir Bhatti (20961974)

“…The pipeline integrates established open-source tools (fastp, BWA-MEM, samtools, iVar, bcftools) and implements <b>codon-aware mutation calling</b> at five canonical RBD positions (R346, S371, K444, F456, F486) relative to NC_045512.2. …”