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.
transforms the information hidden in a microarray experiment into a meaningful
landscape of drugs providing an “enlightened” view of them.
A Tutorial or an example of Mantra Workflow can be displayed in order to understand the functioning of the different workspaces.
Tools and Informations
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.
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)
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. Abstract Pdf
According to the Hindu tradition a Mantra is a sound, syllable, word or group of
capable of creating “spiritual transformation”.
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).
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