BalestraWeb: Efficient online evaluation of drug-target interactions

Murat Can Cobanoglu, Zoltán N. Oltvai, D. Lansing Taylor, Ivet Bahar

Research output: Contribution to journalArticlepeer-review

22 Scopus citations


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 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.

Original languageEnglish (US)
Pages (from-to)131-133
Number of pages3
Issue number1
StatePublished - Jan 1 2015
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2014 The Author. Published by Oxford University Press.


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