Department of Modeling of Biological Processes, University of Heidelberg, Im Neuenheimer Feld 267, 69120 Heidelberg, Germany.
Bioinformatics. 2009 Nov 1;25(21):2816-23. doi: 10.1093/bioinformatics/btp451. Epub 2009 Jul 24.
The growing complexity of biochemical models asks for means to rationally dissect the networks into meaningful and rather independent subnetworks. Such foregoing should ensure an understanding of the system without any heuristics employed. Important for the success of such an approach is its accessibility and the clarity of the presentation of the results.
In order to achieve this goal, we developed a method which is a modification of the classical approach of time-scale separation. This modified method as well as the more classical approach have been implemented for time-dependent application within the widely used software COPASI. The implementation includes different possibilities for the representation of the results including 3D-visualization.
The methods are included in COPASI which is free for academic use and available at www.copasi.org.
irina.surovtsova@bioquant.uni-heidelberg.de
Supplementary data are available at Bioinformatics online.
生化模型的日益复杂性要求有合理的方法将网络分割成有意义且相对独立的子网。这种方法应该可以在不使用任何启发式方法的情况下确保对系统的理解。这种方法的成功与否取决于其可访问性以及结果呈现的清晰程度。
为了实现这一目标，我们开发了一种方法，该方法是对经典时标分离方法的改进。这种改进后的方法以及更经典的方法已在广泛使用的 COPASI 软件中实现了针对时变应用的功能。该实现包括不同的结果表示形式的可能性，包括 3D 可视化。
该方法包含在 COPASI 中，COPASI 可免费用于学术用途，并可在 www.copasi.org 上获得。
irina.surovtsova@bioquant.uni-heidelberg.de
补充数据可在 Bioinformatics 在线获得。
