This record contains the data and model files required to reproduce the analyses and figures in the accompanying GitHub repository for the manuscript “Overcoming systematic data biases enables accurat

Zenodo2026-05-21 更新130

Additional file 5 of GraphKM: machine and deep learning for KM prediction of wildtype and mutant enzymes

酶动力学预测

特征编码

Additional file 5. The one-hot encodings of Kegg compound ID.

NIAID Data Ecosystem60

CatPred: A comprehensive framework for deep learning in vitro enzyme kinetic parameters

酶动力学预测

生物信息学

Raw data for figures of the manuscript and supplementary information

DataCite Commons2025-03-01 更新40

Additional file 4 of GraphKM: machine and deep learning for KM prediction of wildtype and mutant enzymes

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Additional file 4 of GraphKM: machine and deep learning for KM prediction of wildtype and mutant enzymes

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