Physiochemical prediction.

NIAID Data Ecosystem2026-03-11 收录

ADME预测

配体物理化学性质

数据链接：

https://figshare.com/articles/dataset/Physiochemical_prediction_/9683816 数据链接链接失效反馈

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资源简介：

Physiochemical prediction of GEN and CHY ligands as predicted by Swiss ADME and FAFDrugs4 server.

创建时间：

2019-08-19

sj-xls-2-jbx-10.1177_24725552211017520 for Validating ADME QSAR Models Using Marketed Drugs

ADME预测

药物发现

sj-xls-2-jbx-10.1177_24725552211017520 for Validating ADME QSAR Models Using Marketed Drugs by Vishal Siramshetty, Jordan Williams, Ðắc-Trung Nguyễn, Jorge Neyra, Noel Southall, Ewy Mathé, Xin Xu and

DataCite Commons2024-08-28 更新80

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

ADME预测

天然产物药代动力学

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

Figshare2025-03-10 更新50

Calculated physicochemical properties and ADME parameters.

ADME预测

化学性质计算

1) Pipeline Pilot [32] 2) VolSurf+ [36] Calculated physicochemical properties and ADME parameters.

NIAID Data Ecosystem40

ADME Prediction with KNIME: Development and Validation of a Publicly Available Workflow for the Prediction of Human Oral Bioavailability

ADME预测

口服生物利用度计算

In silico prediction of human oral bioavailability is a relevant tool for the selection of potential drug candidates and for the rejection of those molecules with less probability of success during th

NIAID Data Ecosystem60

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

ADME预测

药物发现计算建模

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 developm

Taylor & Francis Group2019-02-16 更新40

Physiochemical prediction.

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