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Bioinformatics. 2015 Jan 1;31(1):131-3. doi: 10.1093/bioinformatics/btu599. Epub 2014 Sep 5.

BalestraWeb: efficient online evaluation of drug-target interactions.

Author information

1
Department of Computational and Systems Biology, University of Pittsburgh, School of Medicine, Pittsburgh, PA, The University of Pittsburgh Drug Discovery Institute, Pittsburgh, PA 15260 and Department of Pathology, University of Pittsburgh, School of Medicine, Pittsburgh, PA 15213, USA Department of Computational and Systems Biology, University of Pittsburgh, School of Medicine, Pittsburgh, PA, The University of Pittsburgh Drug Discovery Institute, Pittsburgh, PA 15260 and Department of Pathology, University of Pittsburgh, School of Medicine, Pittsburgh, PA 15213, USA.
2
Department of Computational and Systems Biology, University of Pittsburgh, School of Medicine, Pittsburgh, PA, The University of Pittsburgh Drug Discovery Institute, Pittsburgh, PA 15260 and Department of Pathology, University of Pittsburgh, School of Medicine, Pittsburgh, PA 15213, USA.

Abstract

SUMMARY:

BalestraWeb is an online server that allows users to instantly make predictions about the potential occurrence of interactions between any given drug-target pair, or predict the most likely interaction partners of any drug or target listed in the DrugBank. It also permits users to identify most similar drugs or most similar targets based on their interaction patterns. Outputs help to develop hypotheses about drug repurposing as well as potential side effects.

AVAILABILITY AND IMPLEMENTATION:

BalestraWeb is accessible at http://balestra.csb.pitt.edu/. The tool is built using a probabilistic matrix factorization method and DrugBank v3, and the latent variable models are trained using the GraphLab collaborative filtering toolkit. The server is implemented using Python, Flask, NumPy and SciPy.

PMID:
25192741
PMCID:
PMC4271144
DOI:
10.1093/bioinformatics/btu599
[Indexed for MEDLINE]
Free PMC Article

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