Parameter estimation in large-scale systems biology models: a parallel and self-adaptive cooperative strategy
详细信息 查看全文
- 作者：David R. Penas ; Patricia González ; Jose A. Egea ; Ramón Doallo…
- 关键词：Dynamic models ; Parameter estimation ; Global optimization ; Metaheuristics ; Parallelization
- 刊名：BMC Bioinformatics
- 出版年：2017
- 出版时间：December 2017
- 年：2017
- 卷：18
- 期：1
- 全文大小：1967KB
- 刊物主题：Bioinformatics; Microarrays; Computational Biology/Bioinformatics; Computer Appl. in Life Sciences; Algorithms;
- 出版者：BioMed Central
- ISSN：1471-2105
- 卷排序：18
文摘
BackgroundThe development of large-scale kinetic models is one of the current key issues in computational systems biology and bioinformatics. Here we consider the problem of parameter estimation in nonlinear dynamic models. Global optimization methods can be used to solve this type of problems but the associated computational cost is very large. Moreover, many of these methods need the tuning of a number of adjustable search parameters, requiring a number of initial exploratory runs and therefore further increasing the computation times.