Programming biological models in Python using PySB.

Programming biological models in Python using PySB.
复制标题

使用PYSB在Python中编程生物模型。

DOI:
10.1038/msb.2013.1
复制
发表时间:
2013
影响因子:
9.9
通讯作者:
--
中科院分区:
生物学1区
文献类型:
--
作者:

文献摘要

参考文献

被引文献

相似文献

数学方程是生物网络建模的基础,但是随着网络变得越来越大并且经常修改,直接管理方程或将先前开发的模型联合收割机组合起来变得困难。创建图形标准、基于规则的语言和集成软件工作台的多项同时努力旨在简化生物建模,但没有一项完全满足透明、可扩展和可重用模型的需求。在本文中,我们描述了PySB,一种方法,在这种方法中,模型不仅使用程序创建,它们就是程序。PySB借鉴了little B和ProMot的编程建模概念,基于规则的语言BioNetGen和Kappa以及不断增长的Python数值工具库。PySB的核心是一个宏库,它编码了常见的生物化学行为,如结合、催化和聚合,使得使用高级的、面向行为的词汇表来构建详细的模型成为可能。作为Python程序,PySB模型利用了开源软件社区的工具和实践,大大提高了我们分发和管理生化假设测试工作的能力。我们使用新的和以前发表的细胞凋亡模型来说明这些想法。
Mathematical equations are fundamental to modeling biological networks, but as networks get large and revisions frequent, it becomes difficult to manage equations directly or to combine previously developed models. Multiple simultaneous efforts to create graphical standards, rule-based languages, and integrated software workbenches aim to simplify biological modeling but none fully meets the need for transparent, extensible, and reusable models. In this paper we describe PySB, an approach in which models are not only created using programs, they are programs. PySB draws on programmatic modeling concepts from little b and ProMot, the rule-based languages BioNetGen and Kappa and the growing library of Python numerical tools. Central to PySB is a library of macros encoding familiar biochemical actions such as binding, catalysis, and polymerization, making it possible to use a high-level, action-oriented vocabulary to construct detailed models. As Python programs, PySB models leverage tools and practices from the open-source software community, substantially advancing our ability to distribute and manage the work of testing biochemical hypotheses. We illustrate these ideas using new and previously published models of apoptosis.
DOI: 10.1371/journal.pbio.0060299
发表时间: 2008-12-02
期刊: PLoS biology
影响因子: 9.8
作者:
Albeck JG;Burke JM;Spencer SL;Lauffenburger DA;Sorger PK
通讯作者: Sorger PK
DOI: 10.1016/j.febslet.2007.09.063
发表时间: 2007-10-30
期刊: FEBS LETTERS
影响因子: 3.5
作者:
Chen, Chun;Cui, Jun;Shen, Pingping
通讯作者: Shen, Pingping
DOI: 10.1073/pnas.0809908106
发表时间: 2009-04-21
影响因子: 11.1
作者:
Feret, Jerome;Danos, Vincent;Fontana, Walter
通讯作者: Fontana, Walter
DOI: 10.1016/j.ccr.2006.03.027
发表时间: 2006-05-01
期刊: CANCER CELL
影响因子: 50.3
作者:
Certo, Michael;Moore, Victoria Del Gaizo;Letai, Anthony
通讯作者: Letai, Anthony
DOI: 10.1038/msb.2008.74
发表时间: 2009
影响因子: 9.9
作者:
Chen, William W.;Schoeberl, Birgit;Jasper, Paul J.;Niepel, Mario;Nielsen, Ulrik B.;Lauffenburger, Douglas A.;Sorger, Peter K.
通讯作者: Sorger, Peter K.