计算机科学
模块化(生物学)
SBML公司
本体论
重新使用
可视化
理论计算机科学
数据挖掘
分布式计算
生物
认识论
操作系统
XML
遗传学
哲学
标记语言
生态学
作者
Michael L. Blinov,Oliver Ruebenacker,Ion I. Moraru
出处
期刊:Iet Systems Biology
[Institution of Engineering and Technology]
日期:2008-09-15
卷期号:2 (5): 363-368
被引量:26
标识
DOI:10.1049/iet-syb:20080092
摘要
Assembly of quantitative models of large complex networks brings about several challenges. One of them is the combinatorial complexity, where relatively few signalling molecules can combine to form thousands or millions of distinct chemical species. A receptor that has several separate phosphorylation sites can exist in hundreds of different states, many of which must be accounted for individually when simulating the time course of signalling. When assembly of protein complexes is being included, the number of distinct molecular species can easily increase by a few orders of magnitude. Validation, visualisation and understanding the network can become intractable. Another challenge appears when the modeller needs to recast or grow a model. Keeping track of changes and adding new elements present a significant difficulty. An approach to solve these challenges within the virtual cell (VCell) is described. Using (i) automatic extraction from pathway databases of model components (http://vcell.org/biopax) and (ii) rules of interactions that serve as reaction network generators (http://vcell.org/bionetgen), a way is provided for semi-automatic generation of quantitative mathematical models that also facilitates the reuse of model elements. In this approach, kinetic models of large, complex networks can be assembled from separately constructed modules, either directly or via rules. To implement this approach, the strength of several related technologies is combined: the BioPAX ontology, the BioNetGen rule-based description of molecular interactions and the VCell modelling and simulation framework.
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