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Mario Miglietta

dblp:146/9814 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2014
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › drug discovery
drug mode of action analysis
0.212014
Mantra 2.0: an online collaborative resource for drug mode of action and repurposing by network analysis · Bioinform. 2014
Bioinformatics and computational biology › drug discovery
drug repurposing
0.112014
Mantra 2.0: an online collaborative resource for drug mode of action and repurposing by network analysis · Bioinform. 2014

Methods — techniques the papers use, named apart from their topics

transcriptional profile similarity · 0.2network analysis · 0.2
YearPublicationVenuePosition
2014 Mantra 2.0: an online collaborative resource for drug mode of action and repurposing by network analysis
abstract
SUMMARY: Elucidation of molecular targets of a compound [mode of action (MoA)] and its off-targets is a crucial step in drug development. We developed an online collaborative resource (MANTRA 2.0) that supports this process by exploiting similarities between drug-induced transcriptional profiles. Drugs are organized in a network of nodes (drugs) and edges (similarities) highlighting 'communities' of drugs sharing a similar MoA. A user can upload gene expression profiles before and after drug treatment in one or multiple cell types. An automated processing pipeline transforms the gene expression profiles into a unique drug 'node' embedded in the drug-network. Visual inspection of the neighbouring drugs and communities helps in revealing its MoA and to suggest new applications of known drugs (drug repurposing). MANTRA 2.0 allows storing and sharing user-generated network nodes, thus making MANTRA 2.0 a collaborative ever-growing resource. AVAILABILITY AND IMPLEMENTATION: The web tool is freely available for academic use at http://mantra.tigem.it.
Diego Carrella, Francesco Napolitano, Rossella Rispoli, Mario Miglietta, Annamaria Carissimo, Luisa Cutillo, Francesco Sirci, Francesco Gregoretti, Diego di Bernardo
Bioinform.4