Metabolic Network Prediction of Drug Side Effects
نویسندگان
چکیده
منابع مشابه
Metabolic Network Prediction of Drug Side Effects.
Drug side effects levy a massive cost on society through drug failures, morbidity, and mortality cases every year, and their early detection is critically important. Here, we describe the array of model-based phenotype predictors (AMPP), an approach that leverages medical informatics resources and a human genome-scale metabolic model (GSMM) to predict drug side effects. AMPP is substantially pr...
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MOTIVATION Identifying the emergence and underlying mechanisms of drug side effects is a challenging task in the drug development process. This underscores the importance of system-wide approaches for linking different scales of drug actions; namely drug-protein interactions (molecular scale) and side effects (phenotypic scale) toward side effect prediction for uncharacterized drugs. RESULTS ...
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Drug co-prescription (or drug combination) is a therapeutic strategy widely used as it may improve efficacy and reduce side-effect (SE). Since it is impractical to screen all possible drug combinations for every indication, computational methods have been developed to predict new combinations. In this study, we describe a novel approach that utilizes clinical SEs from post-marketing surveillanc...
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ژورنال
عنوان ژورنال: Cell Systems
سال: 2016
ISSN: 2405-4712
DOI: 10.1016/j.cels.2016.03.001