Drug-target interaction prediction through domain-tuned network-based inference. Alaimo, S., Pulvirenti, A., Giugno, R., & Ferro, A. Bioinformatics, 29(16):2004--2008, Aug, 2013.
doi  abstract   bibtex   
MOTIVATION: The identification of drug-target interaction (DTI) represents a costly and time-consuming step in drug discovery and design. Computational methods capable of predicting reliable DTI play an important role in the field. Recently, recommendation methods relying on network-based inference (NBI) have been proposed. However, such approaches implement naive topology-based inference and do not take into account important features within the drug-target domain. RESULTS: In this article, we present a new NBI method, called domain tuned-hybrid (DT-Hybrid), which extends a well-established recommendation technique by domain-based knowledge including drug and target similarity. DT-Hybrid has been extensively tested using the last version of an experimentally validated DTI database obtained from DrugBank. Comparison with other recently proposed NBI methods clearly shows that DT-Hybrid is capable of predicting more reliable DTIs. AVAILABILITY: DT-Hybrid has been developed in R and it is available, along with all the results on the predictions, through an R package at the following URL: http://sites.google.com/site/ehybridalgo/.
@article{Alaimo:2013ev,
	Abstract = {MOTIVATION: The identification of drug-target interaction (DTI) represents a costly and time-consuming step in drug discovery and design. Computational methods capable of predicting reliable DTI play an important role in the field. Recently, recommendation methods relying on network-based inference (NBI) have been proposed. However, such approaches implement naive topology-based inference and do not take into account important features within the drug-target domain.
RESULTS: In this article, we present a new NBI method, called domain tuned-hybrid (DT-Hybrid), which extends a well-established recommendation technique by domain-based knowledge including drug and target similarity. DT-Hybrid has been extensively tested using the last version of an experimentally validated DTI database obtained from DrugBank. Comparison with other recently proposed NBI methods clearly shows that DT-Hybrid is capable of predicting more reliable DTIs.
AVAILABILITY: DT-Hybrid has been developed in R and it is available, along with all the results on the predictions, through an R package at the following URL: http://sites.google.com/site/ehybridalgo/.},
	Author = {Alaimo, Salvatore and Pulvirenti, Alfredo and Giugno, Rosalba and Ferro, Alfredo},
	Date-Added = {2015-03-04 15:28:41 +0000},
	Date-Modified = {2015-03-04 15:28:41 +0000},
	Doi = {10.1093/bioinformatics/btt307},
	Journal = {Bioinformatics},
	Journal-Full = {Bioinformatics (Oxford, England)},
	Mesh = {Algorithms; Databases, Pharmaceutical; Drug Discovery; Protein Structure, Tertiary; Proteins},
	Month = {Aug},
	Number = {16},
	Pages = {2004--2008},
	Pmc = {PMC3722516},
	Pmid = {23720490},
	Pst = {ppublish},
	Title = {Drug-target interaction prediction through domain-tuned network-based inference},
	Volume = {29},
	Year = {2013},
	Bdsk-Url-1 = {http://dx.doi.org/10.1093/bioinformatics/btt307}}

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