Bottinelli Arianna, Bassetti Bruno, Lagomarsino Marco Cosentino, Gherardi Marco
Department of Mathematics, Uppsala University, Uppsala, Sweden.
Phys Rev E Stat Nonlin Soft Matter Phys. 2012 Oct;86(4 Pt 1):041919. doi: 10.1103/PhysRevE.86.041919. Epub 2012 Oct 31.
Proteins participating in a protein-protein interaction network can be grouped into homology classes following their common ancestry. Proteins added to the network correspond to genes added to the classes, so the dynamics of the two objects are intrinsically linked. Here we first introduce a statistical model describing the joint growth of the network and the partitioning of nodes into classes, which is studied through a combined mean-field and simulation approach. We then employ this unified framework to address the specific issue of the age dependence of protein interactions through the definition of three different node wiring or divergence schemes. A comparison with empirical data indicates that an age-dependent divergence move is necessary in order to reproduce the basic topological observables together with the age correlation between interacting nodes visible in empirical data. We also discuss the possibility of nontrivial joint partition and topology observables.
参与蛋白质 - 蛋白质相互作用网络的蛋白质可根据其共同祖先被归类为同源类。添加到网络中的蛋白质对应于添加到类中的基因,因此这两个对象的动态本质上是相互关联的。在这里,我们首先引入一个统计模型,该模型描述网络的联合增长以及节点划分为类的过程,并通过均值场和模拟相结合的方法对其进行研究。然后,我们使用这个统一框架,通过定义三种不同的节点连接或分歧方案来解决蛋白质相互作用的年龄依赖性这一具体问题。与经验数据的比较表明,为了重现基本拓扑可观测量以及经验数据中可见的相互作用节点之间的年龄相关性,需要一个与年龄相关的分歧移动。我们还讨论了非平凡联合划分和拓扑可观测量的可能性。