2016
DOI: 10.1186/s12918-016-0326-8
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Drug combinatorics and side effect estimation on the signed human drug-target network

Abstract: BackgroundThe mode of action of a drug on its targets can often be classified as being positive (activator, potentiator, agonist, etc.) or negative (inhibitor, blocker, antagonist, etc.). The signed edges of a drug-target network can be used to investigate the combined mechanisms of action of multiple drugs on the ensemble of common targets.ResultsIn this paper it is shown that for the signed human drug-target network the majority of drug pairs tend to have synergistic effects on the common targets, i.e., drug… Show more

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Cited by 24 publications
(23 citation statements)
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“…[14] Currently, to achieve a comprehensive genotype -phenotype understanding of diseases, many network-centric approaches have been developed and applied. [15] Such network analysis is also performed in drug discovery, notably to decipher new drug-target relationships, [16] drug repositioning, [17] drug side effects [18] or compound promiscuity. [19] More recently, network-based approaches have been considered at the molecular level.…”
Section: Introductionmentioning
confidence: 99%
“…[14] Currently, to achieve a comprehensive genotype -phenotype understanding of diseases, many network-centric approaches have been developed and applied. [15] Such network analysis is also performed in drug discovery, notably to decipher new drug-target relationships, [16] drug repositioning, [17] drug side effects [18] or compound promiscuity. [19] More recently, network-based approaches have been considered at the molecular level.…”
Section: Introductionmentioning
confidence: 99%
“…Among them, 32 and 17 were reported in the literature for efficiently treating breast cancer and lung cancer, respectively. In this work, to analyze the risk assessment of cancer patients, the human drug-target network with positive and negative interactions information was used to add another functional element to the network-based investigation of drug-target interactions, including the activation, inhibition, and pharmacological actions of drug-gene interactions (Torres and Altafini 2016).…”
Section: Collection Of Benchmark Datasets and Reference Networkmentioning
confidence: 99%
“…In this section, we introduce the method for calculating the side effect score of a given drug pair on the drug-target network (Torres and Altafini 2016). The classification of drug actions into positive and negative modes of action allowed us to characterize the effect of multiple drugs acting on the targets.…”
Section: Quantification Of Side Effect Scores On Targetsmentioning
confidence: 99%
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“…In a food web instead, the state x i (t) can denote the population of a species and a control objective could be to preserve biodiversity. Depending on the context, many are the possible ways to define control inputs on networks, from traffic lights in traffic networks (Tewolde, 2012) to drugs in biological networks (Torres and Altafini, 2016), from dams in irrigation networks (Mareels et al, 2005) to opinion makers in social networks, etc.…”
Section: Introductionmentioning
confidence: 99%