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In silico toxicology: computational methods for the prediction of chemical toxicityMapping drug physico-chemical features to pathway activity reveals molecular networks linked to toxicity outcomeComputational tools and resources for metabolism-related property predictions. 1. Overview of publicly available (free and commercial) databases and softwareIn Silico Augmentation of the Drug Development Pipeline: Examples from the study of Acute Inflammation.Adaptation of high-throughput screening in drug discovery-toxicological screening tests.Current Approaches for Investigating and Predicting Cytochrome P450 3A4-Ligand InteractionsExploring the ligand-protein networks in traditional chinese medicine: current databases, methods, and applicationsPersistence and dioxin-like toxicity of carbazole and chlorocarbazoles in soil.In Silico Study and Bioprospection of the Antibacterial and Antioxidant Effects of Flavone and Its Hydroxylated Derivatives.Modern methodologies and tools for human hazard assessment of chemicalsA systematic study of chemogenomics of carbohydrates.Endocrine Disruption at the Androgen Receptor: Employing Molecular Dynamics and Docking for Improved Virtual Screening and Toxicity Prediction.In Silico ADME/Tox Predictions
P2860
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P2860
description
2006 nî lūn-bûn
@nan
2006年の論文
@ja
2006年論文
@yue
2006年論文
@zh-hant
2006年論文
@zh-hk
2006年論文
@zh-mo
2006年論文
@zh-tw
2006年论文
@wuu
2006年论文
@zh
2006年论文
@zh-cn
name
The challenge of predicting drug toxicity in silico.
@ast
The challenge of predicting drug toxicity in silico.
@en
type
label
The challenge of predicting drug toxicity in silico.
@ast
The challenge of predicting drug toxicity in silico.
@en
prefLabel
The challenge of predicting drug toxicity in silico.
@ast
The challenge of predicting drug toxicity in silico.
@en
P2093
P2860
P1476
The challenge of predicting drug toxicity in silico.
@en
P2093
Angelo Vedani
Markus A Lill
Max Dobler
P2860
P304
P356
10.1111/J.1742-7843.2006.PTO_471.X
P577
2006-09-01T00:00:00Z