Name
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. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1007/s10852-009-9118-0 | J. Math. Model. Algorithms |
Keywords | Field | DocType |
biochemical networks · drug design · mathematical modeling · bi-level programming,drug design,drug targeting,cell growth,cellular network,mathematical model,structure function,biological network | Biological network,Gene Deletions,Drug target,Cellular network,Artificial intelligence,Computational biology,Bioinformatics,Mathematical model,Machine learning,Mathematics,Network structure | Journal |
Volume | Issue | ISSN |
9 | 1 | 1572-9214 |
Citations | PageRank | References |
1 | 0.36 | 9 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Guglielmo Lulli | 1 | 205 | 18.82 |
| Enza Messina | 2 | 214 | 23.18 |
| Francesco Archetti | 3 | 140 | 20.73 |
| Stefano Lanzeni | 4 | 65 | 4.76 |