Mantra 2.0 Mode of Action by NeTwoRk Analysis

 


Overview

According to the Hindu tradition a Mantra is a sound, syllable, word or group of words capable of creating “spiritual transformation”.

Mode of Action by NeTwoRk Analysis (MANTRA) is a computational tool for the analysis of the Mode of Action (MoA) of novel drugs and the identification of known and approved candidates for “drug repositioning”. It is based on network theory and non-parametric statistics on gene expression data. In order to study a novel drug users have to give to MANTRA one or more genome-wide ranked list of genes sorted according to their differential expression in a treatment with the drug. On the basis of this input, MANTRA automatically integrates this novel drug in a huge network of compounds in which the topology reveals similarities and differences in MoA. To make novel hypothesis on known and FDA approved drugs, hence to find “repositionable drugs”, users have just to explore this drug network.

Our MANTRA transforms the information hidden in a microarray experiment into a meaningful landscape of drugs providing an “enlightened” view of them.

Tools and Informations

The MANTRA analysis framework is implemented as a set of MATLAB functions. The online version of MANTRA has been integrated in a customized version of the MEDUSA visualization system (a front-end to the STRING protein interaction database).

Contributors

MANTRA is maintained by di Bernardo Lab members at TeleThon Institute of Genetics and Medicine (TIGEM). MANTRA has been developed by Francesco Iorio. The method has been conceived by Francesco Iorio and Diego di Bernardo.

Contribute to MANTRA expansion

Your experimental data could be permanently integrated in the Drug Network of future MANTRA releases. Please contact us for further informations.

How to cite Mantra

Iorio F, Bosotti R, Scacheri E, Belcastro V, Mithbaokar P, Ferriero R, Murino L, Tagliaferri R, Brunetti-Pierri N, Isacchi A, di Bernardo D. Discovery of drug mode of action and drug repositioning from transcriptional responses. Proc Natl Acad Sci U S A, 2010 August 17; 107: 1462-14626. Online Supporting Information (SI)