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IdopNetwork as a genomic predictor of drug response
Jincan Che1, Yuebo Jin2, Claudia Gragnoli3
1School of Grassland Science, Beijing Forestry University, Beijing 100083, China; Beijing Institute of Mathematical Sciences and Applications, Beijing 101408, China.
Abstract:
Despite being challenging, elucidating the systematic control mechanisms of multifactorial drug responses is crucial for pharmacogenomic research. We describe a new form of statistical mechanics to reconstruct informative, dynamic, omnidirectional, and personalized networks (idopNetworks), which cover all pharmacogenomic factors and their interconnections, interdependence, and mechanistic roles. IdopNetworks can characterize how cell-cell crosstalk is mediated by genes and proteins to shape body-drug interactions and identify key roadmaps of information flow and propagation for determining drug efficacy and toxicity. We argue that idopNetworks could potentially provide insight into the genomic machinery of drug responses and provide scientific guidance for the design of drugs whose potency is maximized at lower doses.
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