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面向生命科学家的布尔网络模拟

Boolean network simulations for life scientists.

作者信息

Albert István, Thakar Juilee, Li Song, Zhang Ranran, Albert Réka

机构信息

Huck Institutes for the Life Sciences, Pennsylvania State University, University Park, Pennsylvania, USA.

出版信息

Source Code Biol Med. 2008 Nov 14;3:16. doi: 10.1186/1751-0473-3-16.

Abstract

Modern life sciences research increasingly relies on computational solutions, from large scale data analyses to theoretical modeling. Within the theoretical models Boolean networks occupy an increasing role as they are eminently suited at mapping biological observations and hypotheses into a mathematical formalism. The conceptual underpinnings of Boolean modeling are very accessible even without a background in quantitative sciences, yet it allows life scientists to describe and explore a wide range of surprisingly complex phenomena. In this paper we provide a clear overview of the concepts used in Boolean simulations, present a software library that can perform these simulations based on simple text inputs and give three case studies. The large scale simulations in these case studies demonstrate the Boolean paradigms and their applicability as well as the advanced features and complex use cases that our software package allows. Our software is distributed via a liberal Open Source license and is freely accessible from http://booleannet.googlecode.com.

摘要

现代生命科学研究越来越依赖于计算解决方案,从大规模数据分析到理论建模。在理论模型中,布尔网络发挥着越来越重要的作用,因为它们非常适合将生物学观察和假设映射到数学形式主义中。即使没有定量科学背景,布尔建模的概念基础也很容易理解,但它使生命科学家能够描述和探索各种惊人的复杂现象。在本文中,我们对布尔模拟中使用的概念进行了清晰的概述,展示了一个可以基于简单文本输入执行这些模拟的软件库,并给出了三个案例研究。这些案例研究中的大规模模拟展示了布尔范式及其适用性,以及我们的软件包所具备的高级功能和复杂用例。我们的软件通过宽松的开源许可进行分发,可从http://booleannet.googlecode.com免费获取。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fd31/2603008/69508fb52731/1751-0473-3-16-1.jpg

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