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JigCell模型构建器:用于创建生化反应网络模型的电子表格界面。

The JigCell model builder: a spreadsheet interface for creating biochemical reaction network models.

作者信息

Vass Marc T, Shaffer Clifford A, Ramakrishnan Naren, Watson Layne T, Tyson John J

机构信息

Department of Computer Science, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061-0106, USA.

出版信息

IEEE/ACM Trans Comput Biol Bioinform. 2006 Apr-Jun;3(2):155-64. doi: 10.1109/TCBB.2006.27.

Abstract

Converting a biochemical reaction network to a set of kinetic rate equations is tedious and error prone. We describe known interface paradigms for inputing models of intracellular regulatory networks: graphical layout (diagrams), wizards, scripting languages, and direct entry of chemical equations. We present the JigCell Model Builder, which allows users to define models as a set of reaction equations using a spreadsheet (an example of direct entry of equations) and outputs model definitions in the Systems Biology Markup Language, Level 2. We present the results of two usability studies. The spreadsheet paradigm demonstrated its effectiveness in reducing the number of errors made by modelers when compared to hand conversion of a wiring diagram to differential equations. A comparison of representatives of the four interface paradigms for a simple model of the cell cycle was conducted which measured time, mouse clicks, and keystrokes to enter the model, and the number of screens needed to view the contents of the model. All four paradigms had similar data entry times. The spreadsheet and scripting language approaches require significantly fewer screens to view the models than do the wizard or graphical layout approaches.

摘要

将生化反应网络转换为一组动力学速率方程既繁琐又容易出错。我们描述了用于输入细胞内调控网络模型的已知接口范例:图形布局(图表)、向导、脚本语言以及化学方程式的直接输入。我们展示了JigCell模型构建器,它允许用户使用电子表格(方程式直接输入的一个示例)将模型定义为一组反应方程式,并以系统生物学标记语言第2级输出模型定义。我们展示了两项可用性研究的结果。与将接线图手动转换为微分方程相比,电子表格范例证明了其在减少建模者所犯错误数量方面的有效性。针对细胞周期的一个简单模型,对四种接口范例的代表进行了比较,该比较测量了输入模型所需的时间、鼠标点击次数和击键次数,以及查看模型内容所需的屏幕数量。所有四种范例的数据输入时间相似。与向导或图形布局方法相比,电子表格和脚本语言方法查看模型所需的屏幕显著更少。

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