Biochemical networks are a particular kind of biological networks which describe the cell metabolism and regulate various biological functions, from biochemical pathways to cell growth. The relationship between structure, function and regulation in complex cellular networks is still a largely open question. This complexity calls for proper mathematical models and methods relating network structure and functional properties. In this paper we focus on the problem of drug targets' identification by detecting network alteration strategies which lead to a cell functionality loss. We propose a mathematical model, based on a bi-level programming formulation, to obtain the minimum cost disruption policy through the identification of specific gene deletions. These deletions represent drug target identification of new drug treatments for hindering bacterial infections. © 2009 Springer Science+Business Media B.V.
Lulli, G., Messina, V., Archetti, F., Lanzeni, S. (2010). A mathematical model for optimal functional disruption of biochemical networks. JOURNAL OF MATHEMATICAL MODELLING AND ALGORITHMS, 9(1), 19-37 [10.1007/s10852-009-9118-0].
A mathematical model for optimal functional disruption of biochemical networks
LULLI, GUGLIELMO;MESSINA, VINCENZINA;ARCHETTI, FRANCESCO ANTONIO;LANZENI, STEFANO
2010
Abstract
Biochemical networks are a particular kind of biological networks which describe the cell metabolism and regulate various biological functions, from biochemical pathways to cell growth. The relationship between structure, function and regulation in complex cellular networks is still a largely open question. This complexity calls for proper mathematical models and methods relating network structure and functional properties. In this paper we focus on the problem of drug targets' identification by detecting network alteration strategies which lead to a cell functionality loss. We propose a mathematical model, based on a bi-level programming formulation, to obtain the minimum cost disruption policy through the identification of specific gene deletions. These deletions represent drug target identification of new drug treatments for hindering bacterial infections. © 2009 Springer Science+Business Media B.V.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.