SGER: Dynamical Models of Gene Networks in Development.

SGER：发展中基因网络的动态模型。

• 批准号: 9732702
• 负责人: Garrett Odell
• 金额: $ 4.23万
• 依托单位: University of Washington
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1998
• 资助国家: 美国
• 起止时间: 1998-01-01 至 1999-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9732702&HistoricalAwards=false
• 关键词: SGER; Dynamical; Models; Gene; Networks

O'Dell 9732702 The goals of this project are three-fold: To develop a mathematical framework and computer software for representing and solving differential equation models of gene networks, to assemble a minimal model of the segment polarity gene network of Drosophila melanogaster and to test and refine that model against results in the literature and laboratory experiments, adding components to the model as necessary. Molecular genetics has produced a growing wealth of data on a host of functionally important genes. These data present both an opportunity and a serious challenge to biologists seeking to explain developmental mechanisms. Most, and maybe all, developmentally important genes act within dynamic networks whose essential behaviors are determined by complex webs of interaction among their constituents. Because of their dynamic nature, these essential behaviors cannot be directly inferred from the simple arrow diagrams that biologists typically use to summarize their experiments. The resolution of the actual dynamic interactions occurring simultaneously within even very small networks into accurate predictions of overall network behavior is not possible without the use of computer tools. Thus, computer models offer a powerful and unique approach to analyzing the behavior of such complex dynamic networks. The goal of this proposal is to develop and illustrate a general computer modeling approach that can be generally used to study gene networks in many different contexts. The basis of this approach is to formulate equations describing how the concentration of each network constituent varies continuously in time as a function of its interactions within the network, and then use them to explore the network's behavior. The segment polarity gene network in Drosophila which establishes patterned cell fates across the cellular blastoderm will be used as a model.

O'Dell 9732702 该项目的目标有三个：开发用于表示和求解基因网络微分方程模型的数学框架和计算机软件，组装果蝇片段极性基因网络的最小模型，并根据文献和实验室实验的结果测试和完善该模型，根据需要向模型添加组件。 分子遗传学已经产生了关于许多功能重要基因的越来越丰富的数据。这些数据对于寻求解释发育机制的生物学家来说既是机遇也是严峻的挑战。大多数（也许是全部）对发育至关重要的基因在动态网络中发挥作用，其基本行为是由其成分之间复杂的相互作用网络决定的。由于其动态性质，这些基本行为不能从生物学家通常用来总结实验的简单箭头图直接推断出来。如果不使用计算机工具，就不可能将即使在非常小的网络中同时发生的实际动态交互解析为对整体网络行为的准确预测。因此，计算机模型提供了一种强大且独特的方法来分析此类复杂动态网络的行为。该提案的目标是开发和说明一种通用计算机建模方法，该方法可普遍用于研究许多不同背景下的基因网络。这种方法的基础是制定方程，描述每个网络成分的浓度如何随时间连续变化，作为其在网络内相互作用的函数，然后使用它们来探索网络的行为。果蝇中的片段极性基因网络将被用作模型，该网络在细胞胚盘中建立了模式化的细胞命运。