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The increasing amount of -omics data leads to development of models to interpret and analyse them. A common approach consists in representing data as PPI Networks. These models can be very complex and informatics tools are needed to analyse them. In this abstract, we present MTopGO, an algorithm of module detection specific for PPI Network, exploiting both the network topological information and the Gene Ontology (GO) knowledge about network proteins. MTopGO output consists in a network partition, where each obtained cluster is labelled with a specific GO term describing its biological nature. In a single step, MTopGO performs a double PPI network analysis; from a topological perspective, through the individuation of a meaningful network partition and, from a biological perspective, through the selection of significant GO terms describing the biological role of network proteins.
This is an abstract which has been accepted for the NETTAB 2017 Workshop