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.

Recommendation Techniques for Drug–Target Interaction Prediction and Drug Repositioning

Alaimo S;PULVIRENTI, ALFREDO
2016-01-01

Abstract

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.
2016
978-1-4939-3570-3
Drug–target interaction prediction; Drug combination prediction ; Drug repositioning
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11769/82593
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