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A mathematical model for optimal functional disruption of biochemical networks

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A mathematical model for optimal functional disruption of biochemical networks. / Lulli, Guglielmo; Messina, Enza; Archetti, Francesco et al.
In: Journal of Mathematical Modelling and Algorithms, Vol. 9, No. 1, 03.2010, p. 19-37.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Lulli, G, Messina, E, Archetti, F & Lanzeni, S 2010, 'A mathematical model for optimal functional disruption of biochemical networks', Journal of Mathematical Modelling and Algorithms, vol. 9, no. 1, pp. 19-37. https://doi.org/10.1007/s10852-009-9118-0

APA

Lulli, G., Messina, E., 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. https://doi.org/10.1007/s10852-009-9118-0

Vancouver

Lulli G, Messina E, Archetti F, Lanzeni S. A mathematical model for optimal functional disruption of biochemical networks. Journal of Mathematical Modelling and Algorithms. 2010 Mar;9(1):19-37. Epub 2009 Nov 7. doi: 10.1007/s10852-009-9118-0

Author

Lulli, Guglielmo ; Messina, Enza ; Archetti, Francesco et al. / A mathematical model for optimal functional disruption of biochemical networks. In: Journal of Mathematical Modelling and Algorithms. 2010 ; Vol. 9, No. 1. pp. 19-37.

Bibtex

@article{4a5dda44eb6d49e78f2e6844eb0eb20e,
title = "A mathematical model for optimal functional disruption of biochemical networks",
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.",
keywords = "Bi-level programming, Biochemical networks, Drug design, Mathematical modeling",
author = "Guglielmo Lulli and Enza Messina and Francesco Archetti and Stefano Lanzeni",
year = "2010",
month = mar,
doi = "10.1007/s10852-009-9118-0",
language = "English",
volume = "9",
pages = "19--37",
journal = "Journal of Mathematical Modelling and Algorithms",
issn = "1570-1166",
publisher = "Springer Netherlands",
number = "1",

}

RIS

TY - JOUR

T1 - A mathematical model for optimal functional disruption of biochemical networks

AU - Lulli, Guglielmo

AU - Messina, Enza

AU - Archetti, Francesco

AU - Lanzeni, Stefano

PY - 2010/3

Y1 - 2010/3

N2 - 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.

AB - 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.

KW - Bi-level programming

KW - Biochemical networks

KW - Drug design

KW - Mathematical modeling

U2 - 10.1007/s10852-009-9118-0

DO - 10.1007/s10852-009-9118-0

M3 - Journal article

AN - SCOPUS:76549133476

VL - 9

SP - 19

EP - 37

JO - Journal of Mathematical Modelling and Algorithms

JF - Journal of Mathematical Modelling and Algorithms

SN - 1570-1166

IS - 1

ER -