Pioneering topological methods for network-based drug–target prediction by exploiting a brain-network self-organization theory

@inproceedings{Durn2018PioneeringTM,
  title={Pioneering topological methods for network-based drug–target prediction by exploiting a brain-network self-organization theory},
  author={Claudio Dur{\'a}n and Simone Daminelli and Josephine Maria Thomas and V. Joachim Haupt and Michael Schroeder and Carlo Vittorio Cannistraci},
  booktitle={Briefings in Bioinformatics},
  year={2018}
}
The bipartite network representation of the drug-target interactions (DTIs) in a biosystem enhances understanding of the drugs' multifaceted action modes, suggests therapeutic switching for approved drugs and unveils possible side effects. As experimental testing of DTIs is costly and time-consuming, computational predictors are of great aid. Here, for the first time, state-of-the-art DTI supervised predictors custom-made in network biology were compared-using standard and innovative validation… CONTINUE READING

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