We propose and systematically compare different gene network combination algorithms to experimentally assess the effect of network integration in the context of gene prioritization. An extensive application of network-based gene prioritization methods to 725 MeSH diseases shows how to apply network integration to find novel candidate disease genes predicted with high accuracy and reliability.
Network integration boosts disease gene prioritization / G. Valentini, A. Paccanaro, H. Vierci, A. Romero, M. Re. ((Intervento presentato al convegno Network Biology SIG 2013 ISMB 2013 tenutosi a Berlin nel 2013.
Network integration boosts disease gene prioritization
G. ValentiniPrimo
;M. ReUltimo
2013
Abstract
We propose and systematically compare different gene network combination algorithms to experimentally assess the effect of network integration in the context of gene prioritization. An extensive application of network-based gene prioritization methods to 725 MeSH diseases shows how to apply network integration to find novel candidate disease genes predicted with high accuracy and reliability.
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