English   español  
Please use this identifier to cite or link to this item: http://hdl.handle.net/10261/56218
logo share SHARE logo core CORE   Add this article to your Mendeley library MendeleyBASE

Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL
Exportar a otros formatos:

Parameter estimation in biochemical pathways: A comparison of global optimization methods

AuthorsMoles, Carmen G.; Mendes, Pedro; Banga, Julio R.
Issue Date2003
PublisherCold Spring Harbor Laboratory Press
CitationGenome Research 13: 2467-2474 (2003)
AbstractHere we address the problem of parameter estimation (inverse problem)of nonlinear dynamic biochemical pathways. This problem is stated as a nonlinear programming (NLP)problem subject to nonlinear differential-algebraic constraints. These problems are known to be frequently ill-conditioned and multimodal. Thus, traditional (gradient-based)local optimization methods fail to arrive at satisfactory solutions. To surmount this limitation, the use of several state-of-the-art deterministic and stochastic global optimization methods is explored. A case study considering the estimation of 36 parameters of a nonlinear biochemical dynamic model is taken as a benchmark. Only a certain type of stochastic algorithm, evolution strategies (ES), is able to solve this problem successfully. Although these stochastic methods cannot guarantee global optimality with certainty, their robustness, plus the fact that in inverse problems they have a known lower bound for the cost function, make them the best available candidates
Description8 páginas
Publisher version (URL)http://dx.doi.org/10.1101/gr.1262503
Appears in Collections:(IIM) Artículos
Files in This Item:
There are no files associated with this item.
Show full item record
Review this work

Related articles:

WARNING: Items in Digital.CSIC are protected by copyright, with all rights reserved, unless otherwise indicated.