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PSExplorer: whole parameter space exploration for molecular signaling pathway dynamics

Motivation: Mathematical models of biological systems often have a large number of parameters whose combinational variations can yield distinct qualitative behaviors. Since it is intractable to examine all possible combinations of parameters for non-trivial biological pathways, it is required to hav...

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Detalles Bibliográficos
Autores principales: Tung, Thai Quang, Lee, Doheon
Formato: Texto
Lenguaje:English
Publicado: Oxford University Press 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2944198/
https://www.ncbi.nlm.nih.gov/pubmed/20679335
http://dx.doi.org/10.1093/bioinformatics/btq440
Descripción
Sumario:Motivation: Mathematical models of biological systems often have a large number of parameters whose combinational variations can yield distinct qualitative behaviors. Since it is intractable to examine all possible combinations of parameters for non-trivial biological pathways, it is required to have a systematic strategy to explore the parameter space in a computational way so that dynamic behaviors of a given pathway are estimated. Results: We present PSExplorer, a computational tool for exploring qualitative behaviors and key parameters of molecular signaling pathways. Utilizing the Latin hypercube sampling and a clustering technique in a recursive paradigm, the software enables users to explore the whole parameter space of the models to search for robust qualitative behaviors. The parameter space is partitioned into sub-regions according to behavioral differences. Sub-regions showing robust behaviors can be identified for further analyses. The partitioning result presents a tree structure from which individual and combinational effects of parameters on model behaviors can be assessed and key factors of the models are readily identified. Availability: The software, tutorial manual and test models are available for download at the following address: http://gto.kaist.ac.kr/∼psexplorer Contact: tqtung@kaist.ac.kr; tqtung@gmail.com