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Integrating high-dimensional transcriptomics and image analysis tools into early safety screening (III)

ChEBI2015-12-31 更新2026-07-12 收录

药物安全性预测

多模态毒理学评估

数据链接：

https://www.ebi.ac.uk/biostudies/ArrayExpress/studies/E-GEOD-70614 数据链接链接失效反馈

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资源简介：

Integrating high-dimensional transcriptomics and image analysis tools into early safety screening (III)

应用场景：

创建时间：

2015-12-31

药物性肝损伤遗传学

药物安全性预测

Drug-Induced-Liver-Injury (DILI) is a leading cause of termination in drug development programs and removal of drugs from the market because of inability to identify potential patients prior to clinic

NIAID Data Ecosystem70

MOESM10 of Leveraging 3D chemical similarity, target and phenotypic data in the identification of drug-protein and drug-adverse effect associations

药物重定位

药物安全性预测

Additional file 10: Table S6. Dataset with 338,638 drug-target-adverse effect candidates extracted from the modeling.

Figshare2017-02-21 更新40

How Does the Quality of Phospholipidosis Data Influence the Predictivity of Structural Alerts?

药物安全性预测

磷脂质沉积症

The ability of drugs to induce phospholipidosis (PLD) is linked directly to their molecular substructures: hydrophobic, cyclic moieties with hydrophilic, peripheral amine groups. These structural prop

NIAID Data Ecosystem30

In vitro transcriptomic responses to thioacetamide-S-oxide exposure in human primary hepatocytes, renal tube epithelial, and cardiomyocytes. In vitro transcriptomic responses to thioacetamide-S-oxide exposure in human primary hepatocytes, renal tube epithelial, and cardiomyocytes

毒理转录组学

药物安全性预测

In this study we tested the ability to predict organ injury endpoints from in vitro transcriptomics responses at early time points (9 and 24 hours) after to thioacetamide-S-oxide treatment, the toxic

NIAID Data Ecosystem40

Predicted probabilities of post-IVM SAEs at various L. loa MFD cutoffs.

寄生虫病治疗评估

药物安全性预测

Predicted probabilities of post-IVM SAEs at various L. loa MFD cutoffs.

NIAID Data Ecosystem30