Zhang Mingwu, Ouyang Qi, Stephenson Alan, Kane Michael D, Salt David E, Prabhakar Sunil, Burgner John, Buck Charles, Zhang Xiang
Bindley Bioscience Center, Purdue University, West Lafayette, IN 47907, USA.
BMC Syst Biol. 2008 Feb 29;2:23. doi: 10.1186/1752-0509-2-23.
Systems biology aims to understand biological systems on a comprehensive scale, such that the components that make up the whole are connected to one another and work through dependent interactions. Molecular correlations and comparative studies of molecular expression are crucial to establishing interdependent connections in systems biology. The existing software packages provide limited data mining capability. The user must first generate visualization data with a preferred data mining algorithm and then upload the resulting data into the visualization package for graphic visualization of molecular relations.
Presented is a novel interactive visual data mining application, SysNet that provides an interactive environment for the analysis of high data volume molecular expression information of most any type from biological systems. It integrates interactive graphic visualization and statistical data mining into a single package. SysNet interactively presents intermolecular correlation information with circular and heatmap layouts. It is also applicable to comparative analysis of molecular expression data, such as time course data.
The SysNet program has been utilized to analyze elemental profile changes in response to an increasing concentration of iron (Fe) in growth media (an ionomics dataset). This study case demonstrates that the SysNet software is an effective platform for interactive analysis of molecular expression information in systems biology.
系统生物学旨在全面理解生物系统,使构成整体的各个组件相互连接并通过依赖的相互作用发挥作用。分子相关性以及分子表达的比较研究对于在系统生物学中建立相互依存的联系至关重要。现有的软件包数据挖掘能力有限。用户必须首先使用首选的数据挖掘算法生成可视化数据,然后将生成的数据上传到可视化软件包中以对分子关系进行图形可视化。
本文介绍了一种新颖的交互式可视化数据挖掘应用程序SysNet,它为分析来自生物系统的几乎任何类型的高数据量分子表达信息提供了一个交互式环境。它将交互式图形可视化和统计数据挖掘集成到一个软件包中。SysNet通过圆形和热图布局交互式地呈现分子间的相关信息。它也适用于分子表达数据的比较分析,如时间进程数据。
SysNet程序已被用于分析在生长培养基中(一个离子组学数据集)铁(Fe)浓度增加时元素谱的变化。这个案例研究表明,SysNet软件是系统生物学中分子表达信息交互式分析的有效平台。