Document Detail


Multi-objective mixed integer strategy for the optimisation of biological networks.
MedLine Citation:
PMID:  20500003     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
In this contribution, the authors consider multi-criteria optimisation problems arising from the field of systems biology when both continuous and integer decision variables are involved. Mathematically, they are formulated as mixed-integer non-linear programming problems. The authors present a novel solution strategy based on a global optimisation approach for dealing with this class of problems. Its usefulness and capabilities are illustrated with two metabolic engineering case studies. For these problems, the authors show how the set of optimal solutions (the so-called Pareto front) is successfully and efficiently obtained, providing further insight into the systems under consideration regarding their optimal manipulation.
Authors:
J O H Sendín; O Exler; J R Banga
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't    
Journal Detail:
Title:  IET systems biology     Volume:  4     ISSN:  1751-8849     ISO Abbreviation:  IET Syst Biol     Publication Date:  2010 May 
Date Detail:
Created Date:  2010-05-26     Completed Date:  2010-07-26     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  101301198     Medline TA:  IET Syst Biol     Country:  England    
Other Details:
Languages:  eng     Pagination:  236-48     Citation Subset:  IM    
Affiliation:
Process Engineering Group, Vigo, SpainUniversity of Bayreuth, Department of Computer Science, Bayreuth, Germany. julio@iim.csic.es
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MeSH Terms
Descriptor/Qualifier:
Algorithms*
Animals
Computer Simulation
Humans
Models, Biological*
Proteome / metabolism*
Signal Transduction / physiology*
Chemical
Reg. No./Substance:
0/Proteome

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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