Translating clinical findings into knowledge in drug safety evaluation--drug induced liver injury prediction system (DILIps)
about
In vitro platforms for evaluating liver toxicity.atBioNet--an integrated network analysis tool for genomics and biomarker discovery.Curated human hyperbilirubinemia data and the respective OATP1B1 and 1B3 inhibition predictionsThe primary role of hepatic metabolism in idiosyncratic drug-induced liver injury.Latest advances in predicting DILI in human subjects: focus on biomarkers.Pharmacogenomic biomarkers for personalized medicine.Toward predictive models for drug-induced liver injury in humans: are we there yet?The application of engineered liver tissues for novel drug discovery.In Silico Identification of Proteins Associated with Drug-induced Liver Injury Based on the Prediction of Drug-target Interactions.In silico Prediction of Drug-induced Liver Injury Based on Adverse Drug Reaction Reports.Current limitations and future opportunities for prediction of DILI from in vitro.Identification of Novel Inhibitors of Organic Anion Transporting Polypeptides 1B1 and 1B3 (OATP1B1 and OATP1B3) Using a Consensus Vote of Six Classification Models.In Silico Models for Hepatotoxicity.In silico Prediction of Drug Induced Liver Toxicity Using Substructure Pattern Recognition Method.Chemical and in vitro biological information to predict mouse liver toxicity using recursive random forests.Identifying problematic drugs based on the characteristics of their targetsLabel Propagation Prediction of Drug-Drug Interactions Based on Clinical Side Effects.Systematic prediction of drug combinations based on clinical side-effects.A testing strategy to predict risk for drug-induced liver injury in humans using high-content screen assays and the 'rule-of-two' model.Development of Decision Forest Models for Prediction of Drug-Induced Liver Injury in Humans Using A Large Set of FDA-approved Drugs.The liver toxicity knowledge base: a systems approach to a complex end point.The Liver Toxicity Knowledge Base (LKTB) and drug-induced liver injury (DILI) classification for assessment of human liver injury.Foretelling toxicity: FDA researchers work to predict risk of liver injury from drugs.
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Translating clinical findings into knowledge in drug safety evaluation--drug induced liver injury prediction system (DILIps)
description
2011 nî lūn-bûn
@nan
2011 թուականի Դեկտեմբերին հրատարակուած գիտական յօդուած
@hyw
2011 թվականի դեկտեմբերին հրատարակված գիտական հոդված
@hy
2011年の論文
@ja
2011年論文
@yue
2011年論文
@zh-hant
2011年論文
@zh-hk
2011年論文
@zh-mo
2011年論文
@zh-tw
2011年论文
@wuu
name
Translating clinical findings ...... ury prediction system (DILIps)
@ast
Translating clinical findings ...... ury prediction system (DILIps)
@en
Translating clinical findings ...... ury prediction system (DILIps)
@nl
type
label
Translating clinical findings ...... ury prediction system (DILIps)
@ast
Translating clinical findings ...... ury prediction system (DILIps)
@en
Translating clinical findings ...... ury prediction system (DILIps)
@nl
prefLabel
Translating clinical findings ...... ury prediction system (DILIps)
@ast
Translating clinical findings ...... ury prediction system (DILIps)
@en
Translating clinical findings ...... ury prediction system (DILIps)
@nl
P2093
P2860
P1476
Translating clinical findings ...... ury prediction system (DILIps)
@en
P2093
Reagan Kelly
Zhichao Liu
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P304
P356
10.1371/JOURNAL.PCBI.1002310
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P50
P577
2011-12-01T00:00:00Z