The usage of computational methods in drug discovery is a common practice. More recently, by exploiting the wealth of biological knowledge bases, a novel approach called drug repositioning has raised. Several computational methods are available, and these try to make a high-level integration of all the knowledge in order to discover unknown mechanisms. In this chapter, we review drug–target interaction prediction methods based on a recommendation system. We also give some extensions which go beyond the bipartite network case.
Titolo: | Recommendation Techniques for Drug–Target Interaction Prediction and Drug Repositioning |
Autori interni: | |
Data di pubblicazione: | 2016 |
Rivista: | |
Handle: | http://hdl.handle.net/20.500.11769/82593 |
ISBN: | 978-1-4939-3570-3 |
Appare nelle tipologie: | 2.1 Contributo in volume (Capitolo o Saggio) |
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