Graph theoretical approach to study molecular evolution

本项目主要研究分子进化的图论研究。特别的兴趣包括开发图论方法，模型和算法，用于研究多结构域蛋白质，蛋白质-蛋白质相互作用和其他生物网络。 该项目有以下分专题： 1.基于特征的进化的图论方法。在这里，我们考虑所谓的字符重叠图。这种图的节点是字符，如果两个字符在某个生物体中一起出现，则两个字符之间存在边。了解这个图的属性可以深入了解相应字符的可能进化模式。 2.蛋白质相互作用网络的动力学恢复和表示。我们的方法在很大程度上依赖于图论的重要成果，更具体地说，理论的两个重要的图形家庭：弦图和合作图。通过在我们的建模中使用这两个图族，我们捕获了信号通路的动态和官能团的重叠结构。 3.从蛋白质相互作用网络预测结构域相互作用。我们假设蛋白质-蛋白质相互作用是以一种简约的方式进化的。与简约假设一致，我们确定的相互作用域作为最小的（加权）对，这是必要的解释蛋白质相互作用网络。

This project focuses on graph theoretical study of molecular evolution. Particular interests include developing graph theoretical methods, models, and algorithms for study multidomain proteins, protein-protein interactions and other biological networks. The project has the following subtopics: 1.Graph theoretical approaches to character based evolution. Here we consider the so called character overlap graph. The nodes of such graph are characters and there is an edge between two characters if they occur together in some organism. Understanding of properties of this graph provides insights into possible modes of evolution of the corresponding characters. 2.Recovering and representing the dynamics of protein-protein interaction networks. Our approach relies heavily on important results from graph theory; more specifically, the theory of two important graph families: chordal graphs and co-graphs. By using these two graph families in our modeling, we capture the dynamics of signaling pathways and overlapping structure of functional groups. 3.Predicting domain-domain interactions from protein-protein interaction network. We postulate that protein-protein interactions evolved in a parsimonious way. Consistently with the parsimony postulate, we identify the interacting domain as the smallest (weighted) set of pairs that is necessary to explain the protein interaction network.