Kratz Anton, Tomita Masaru, Krishnan Arun
Institute for Advanced Biosciences, Keio University, 14-1, Baba-Cho, Tsuruoka, Yamagata-ken, 997-0035, Japan.
BMC Bioinformatics. 2008 Dec 16;9:541. doi: 10.1186/1471-2105-9-541.
There has been a lot of interest in recent years focusing on the modeling and simulation of Gene Regulatory Networks (GRNs). However, the evolutionary mechanisms that give rise to GRNs in the first place are still largely unknown. In an earlier work, we developed a framework to analyze the effect of objective functions, input types and starting populations on the evolution of GRNs with a specific emphasis on the robustness of evolved GRNs.
In this work, we present a parallel software package, GeNESiS for the modeling and simulation of the evolution of gene regulatory networks (GRNs). The software models the process of gene regulation through a combination of finite-state and stochastic models. The evolution of GRNs is then simulated by means of a genetic algorithm with the network connections represented as binary strings. The software allows users to simulate the evolution under varying selective pressures and starting conditions. We believe that the software provides a way for researchers to understand the evolutionary behavior of populations of GRNs.
We believe that GeNESiS will serve as a useful tool for scientists interested in understanding the evolution of gene regulatory networks under a range of different conditions and selective pressures. Such modeling efforts can lead to a greater understanding of the network characteristics of GRNs.
近年来，人们对基因调控网络（GRNs）的建模与模拟产生了浓厚兴趣。然而，最初产生GRNs的进化机制在很大程度上仍不为人知。在早期的一项工作中，我们开发了一个框架，用于分析目标函数、输入类型和初始种群对GRNs进化的影响，特别强调进化后的GRNs的稳健性。
在这项工作中，我们展示了一个并行软件包GeNESiS，用于基因调控网络（GRNs）进化的建模与模拟。该软件通过有限状态模型和随机模型的组合对基因调控过程进行建模。然后，借助遗传算法模拟GRNs的进化，网络连接用二进制字符串表示。该软件允许用户在不同的选择压力和初始条件下模拟进化过程。我们相信，该软件为研究人员提供了一种了解GRNs种群进化行为的方法。
我们相信，GeNESiS将成为对在一系列不同条件和选择压力下理解基因调控网络进化感兴趣的科学家的有用工具。此类建模工作有助于更深入地了解GRNs的网络特征。
