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Additional file 3 of Predicting liver cytosol stability of small molecules

NIAID Data Ecosystem2026-03-11 收录

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https://figshare.com/articles/dataset/Additional_file_3_of_Predicting_liver_cytosol_stability_of_small_molecules/12096588 数据链接链接失效反馈

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资源简介：

Additional file 3. External validation results.

应用场景：

创建时间：

2020-04-07

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Characterisation of data resources for in silico modelling: benchmark datasets for ADME properties

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Introduction: The cost of in vivo and in vitro screening of ADME properties of compounds has motivated efforts to develop a range of in silico models. At the heart of the development of any computatio

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In silico ADME analysis of phytoconstituents (S1-S10) identified from J. Marshi rice from Nepal.

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Improved ADME Prediction by Multitask Pretraining on Predicted Data: Insights from the ASAP-Polaris-OpenADMET Blind Challenge

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Absorption, distribution, metabolism, and excretion (ADME) properties are among the key factors in determining the success of lead discovery and optimization campaigns. Fast and accurate prediction of

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Genetic Algorithm-Optimized QSPR Models for Bioavailability, Protein Binding, and Urinary Excretion

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In this work, a genetic algorithm (GA) was applied to build up a set of QSPR (quantitative structure−property relationship) models for human absolute oral bioavailability, plasma protein binding, and

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Additional file 3 of Predicting liver cytosol stability of small molecules

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