MANTRA 2.0
Mode of Action by NeTwoRk Analysis
A computational tool for analyzing drug Mode of Action (MoA) and identifying candidates for drug repositioning through network theory and gene expression analysis.
Overview
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.
Drug Analysis
Analyze novel drugs by integrating genome-wide ranked gene lists into a comprehensive drug network.
Drug Repositioning
Discover new therapeutic applications for known and FDA-approved drugs through network topology analysis.
Getting Started
Tutorial Workflow can be displayed in order to understand the functioning of the different workspaces.
Tools and Information
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.
Contributors
MANTRA is maintained by di Bernardo Lab members at TeleThon Institute of Genetics and Medicine (TIGEM). Developed by Francesco Iorio and Diego di Bernardo.
"According to the Hindu tradition a Mantra is a sound, syllable, word or group of words capable of creating 'spiritual transformation'."
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.
Carrella D, Napolitano F, Rispoli R, Miglietta M, Carissimo A, Cutillo L, Sirci F, Gregoretti F, di Bernardo D. Mantra 2.0: an online collaborative resource for drug mode of action and repurposing by network analysis. Bioinformatics (2014) 30 (12): 1787-1788.
User data are stored permanently in our database and made freely available to everyone in the form of new "nodes" in the drug network (note, however, that the raw transcriptional profiles are never made publicly available).