Representative MSD plots, Fig. 6c,d by Hirotake Udono (21008660)

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)

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

(a) System dynamics: schematic representation of all the reactions in the Tree model, which are aging, reproduction, color cycle, and competition. by Fabricio Cravo (21387854)

Simulated dynamics of the Mutual Annihilation protocol [26]. by Fabricio Cravo (21387854)

Correlation (a) and Mean-Absolute-Error (b) between frequencies at a reference cutoff, δ₀, and different frequencies, , at different cutoff-values, δ_scan ∊ [3... by Guillermo Pérez-Hernández (21156182)

A) Schematic representation of the extended SEIR model, incorporating additional compartments to account for disease-related mortality. by Nicolò Gozzi (8837522)

Modeling lung cancer AST network and its perturbation with a SOX2 degrader. (A) Lung Cancer AST Network and the corresponding stochastic equations. Parameters are , , , , , , , , w... by Ziyan Jin (21021976)

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. …”

PTPC-UHT bounce by David Parry (22169299)

“…</p><p dir="ltr">Included files:</p><ul><li>Python source code (<code>PTPC_UHT_bounce.py</code>)</li><li>Parameter sets for representative runs (α,β,Tcrit,V(T)\alpha, \beta, T_{\mathrm{crit}}, V(T)α,β,Tcrit​,V(T))</li><li>Output arrays of trajectories across multiple bounces</li><li>Multi-panel plots (PNG/PDF) for a(t)a(t)a(t), H(t)H(t)H(t), T(t)T(t)T(t), S(t)S(t)S(t), R(t)R(t)R(t), and ρT\rho_TρT​</li></ul><p dir="ltr">This dataset ensures full reproducibility of the PTPC simulations and provides a starting point for independent verification, parameter exploration, and future model extensions.…”

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

Data for "A hollow fiber membrane permeance evaluation device demonstrating outside-in and inside-out performance differences" by Timothy Warner (20222838)

“…</li><li>Flux decline data generated by the analysis software.</li><li>Plot data derived from the above data sources.</li><li>Python code to generate figures from the plot data.…”

LBQANA python code + Merged Gene Expression Dataset from GSE10810, GSE17907, GSE20711, GSE42568, GSE45827, and GSE61304 for Breast Cancer Biomarker Discovery by M RN (9866504)

Output datasets from ML–assisted bibliometric workflow in African phytochemical metabolomics research by Temitope Omogbene (18615415)

“…</li><li><b>Dataset 1B (sampled_data.xlsx):</b> A stratified random sample generated in Python for pretraining and manual annotation.…”

Segmentation module training details. by Khelina Fedorchuk (19130089)

Fig 3 - Using artificial intelligence tools to automate data extraction for living evidence syntheses by Evan Mitchell (20995743)

Microscopic Detection and Quantification of Microplastic Particles in Environmental Water Samples by Derek Lam (11944213)

“…Image processing algorithms, implemented in Python using adaptive thresholding techniques, were applied to segment particles from the background. …”

Fig 4. - mdciao: Accessible Analysis and Visualization of Molecular Dynamics Simulation Data by Guillermo Pérez-Hernández (21156182)

Map of stations sampled during the 2023 and 2022 cruises along the coastal NESAP. by Brandon J. McNabb (19337538)

“…<p>Markers indicate the type of experiments conducted; black circles denote light manipulations, while stars represent DCMU addition experiments. Red labels denote stations sampled in 2023. …”

Examples of insights derived from iModulons. by Anand V. Sastry (6619310)