Predicting adverse drug reactions using publicly available PubChem BioAssay data
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Drug Repurposing Is a New Opportunity for Developing Drugs against Neuropsychiatric DisordersCheminformatics analysis of the AR agonist and antagonist datasets in PubChemThe coming age of data-driven medicine: translational bioinformatics' next frontierSystematic drug repositioning based on clinical side-effectsNovel data-mining methodologies for adverse drug event discovery and analysisCharacterizing protein domain associations by Small-molecule ligand bindingComputational drug repositioning: from data to therapeutics.An efficient algorithm coupled with synthetic minority over-sampling technique to classify imbalanced PubChem BioAssay data.Web search and data mining of natural products and their bioactivities in PubChemToward enhanced pharmacovigilance using patient-generated data on the internetUnveiling new biological relationships using shared hits of chemical screening assay pairsPredicting adverse side effects of drugsAutomatically detecting workflows in PubChem.Translational bioinformatics embraces big data.PubChem applications in drug discovery: a bibliometric analysisGetting the most out of PubChem for virtual screeningCombining automatic table classification and relationship extraction in extracting anticancer drug-side effect pairs from full-text articles.Automatic construction of a large-scale and accurate drug-side-effect association knowledge base from biomedical literature.Integrating Multiple Evidence Sources to Predict Adverse Drug Reactions Based on a Systems Pharmacology Model.The potential of translational bioinformatics approaches for pharmacology research.Natural Language Processing for EHR-Based Pharmacovigilance: A Structured Review.Traditional chinese medicine-based network pharmacology could lead to new multicompound drug discoveryDetermining molecular predictors of adverse drug reactions with causality analysis based on structure learning.The impact of network biology in pharmacology and toxicology.Detection of Drug-Drug Interactions Inducing Acute Kidney Injury by Electronic Health Records Mining.The role of drug profiles as similarity metrics: applications to repurposing, adverse effects detection and drug-drug interactions.Standard-based comprehensive detection of adverse drug reaction signals from nursing statements and laboratory results in electronic health records.Cheminformatics-aided pharmacovigilance: application to Stevens-Johnson Syndrome.Large-scale prediction of adverse drug reactions using chemical, biological, and phenotypic properties of drugs.Translational bioinformatics: data-driven drug discovery and development.Translational systems pharmacology-based predictive assessment of drug-induced cardiomyopathy.Predicting adverse drug reaction profiles by integrating protein interaction networks with drug structures.Expanding biological space coverage enhances the prediction of drug adverse effects in human using in vitro activity profiles.
P2860
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P2860
Predicting adverse drug reactions using publicly available PubChem BioAssay data
description
2011 nî lūn-bûn
@nan
2011 թուականի Մայիսին հրատարակուած գիտական յօդուած
@hyw
2011 թվականի մայիսին 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
Predicting adverse drug reactions using publicly available PubChem BioAssay data
@ast
Predicting adverse drug reactions using publicly available PubChem BioAssay data
@en
type
label
Predicting adverse drug reactions using publicly available PubChem BioAssay data
@ast
Predicting adverse drug reactions using publicly available PubChem BioAssay data
@en
prefLabel
Predicting adverse drug reactions using publicly available PubChem BioAssay data
@ast
Predicting adverse drug reactions using publicly available PubChem BioAssay data
@en
P2860
P356
P1476
Predicting adverse drug reactions using publicly available PubChem BioAssay data
@en
P2093
P2860
P356
10.1038/CLPT.2011.81
P407
P577
2011-05-25T00:00:00Z