CDI-Type II: Hierarchiacal Modularity in Evolution and Function

该项目将为解决从分子到组织水平的细胞现象建立一个全面的基础设施。该项目的主要贡献是使用生物分子内的域作为功能描述的主要单位。这一目标提出了几个智力挑战，构成了提案的重点：(i)为领域推理构建强大的分析、算法和软件基础设施，以补充现有的（实验）领域数据；（ii）将现有分子相互作用数据解析为域相互作用数据；（iii）开发推断领域相互作用数据的模块化和功能相干性的技术；（四）调查基于域的分析对疾病标记物识别、干预和实验的影响。复杂系统的分析、仿真和设计通常是根据直观的自然组件进行的。然而，出于预测、设计或理解的目的，这样的分析并不总是为复杂系统提供最有力的描述符。这方面的一个例子是线性或可线性复杂系统的正态分析。正常模式是一种数学抽象，但却是对现实物理系统的有力描述。普通模式还在系统的层次和粗粒度描述中定义模块。模块化是生物学的一个标志。破译生物模块，研究它们如何以定量的方式组合产生功能，并描述它们在产生更大表型时的层次结构，可能会建立支配生命系统的基本规律。利用分子和细胞生物学以及算法开发方面的专业知识，这四家机构的合作将专注于开发用于研究和设计生物分子模块的算法、工具和方法。

This project will build a comprehensive infrastructure for resolving cellular phenomena, from the molecular to the tissue level. The key underlying contribution of the project is the use of domains within biomolecules as primary units of functional description. This goal poses several intellectual challenges, which form the focus of the proposal: (i) building robust analytical, algorithmic, and software infrastructure for domain inference to complement existing (experimental) domain data; (ii) resolving existing molecular interaction data into domain interaction data; (iii) developing techniques for inferring modularity and functional coherence in domain interaction data; (iv) investigate implications of domain-based analysis on identification of disease markers, intervention, and experimentation. The analysis, simulation and design of complex systems is often performed in terms of intuitively natural components. However analysis in such terms does not always provide the most powerful descriptor of complex systems, for purposes of prediction, design, or understanding. An example of this is the normal mode analysis of linear or linearizable complex systems. The normal mode is a mathematical abstraction, but is a powerful descriptor of real-life physical systems. Normal modes also define modules in the hierarchical and coarse-grained description of systems. Modularity is a hallmark of biology. Deciphering biological modules, studying how they combine in a quantitative manner to yield function, and describing their hierarchy in producing larger phenotypes, is likely to establish fundamental laws that govern living systems. Leveraging expertise in molecular and cellular biology and algorithm development, this collaboration of four institutions will focus on developing algorithms, tools, and methods for studying and designing biomolecular modules.