Zhang Ruihua, Reinert Gesine
Department of Statistics, University of Oxford, 24-29 St. Giles', Oxford OX1 3LB, UK.
The Alan Turing Institute, London NW1 2DB, UK.
Entropy (Basel). 2024 Sep 25;26(10):813. doi: 10.3390/e26100813.
A better understanding of protein-protein interaction (PPI) networks representing physical interactions between proteins could be beneficial for evolutionary insights as well as for practical applications such as drug development. As a statistical model for PPI networks, duplication-divergence models have been proposed, but they suffer from resulting in either very sparse networks in which most of the proteins are isolated, or in networks which are much denser than what is usually observed, having almost no isolated proteins. Moreover, in real networks, where a gene codes a protein, gene loss may occur. The loss of nodes has not been captured in duplication-divergence models to date. Here, we introduce a new duplication-divergence model which includes node loss. This mechanism results in networks in which the proportion of isolated proteins can take on values which are strictly between 0 and 1. To understand this new model, we apply strong and weak attacks to networks from duplication-divergence models with and without node loss, and compare the results to those obtained when carrying out similar attacks on two real PPI networks of and of . We find that the new model more closely reflects the damage caused by strong and weak attacks found in the PPI networks.
更好地理解代表蛋白质之间物理相互作用的蛋白质-蛋白质相互作用（PPI）网络，可能有助于获得进化方面的见解，以及对药物开发等实际应用有所帮助。作为PPI网络的一种统计模型，已提出了复制-分化模型，但它们存在问题，即要么导致非常稀疏的网络，其中大多数蛋白质是孤立的，要么导致比通常观察到的网络密度大得多的网络，几乎没有孤立蛋白质。此外，在实际网络中，当一个基因编码一种蛋白质时，可能会发生基因丢失。到目前为止，复制-分化模型尚未捕捉到节点的丢失。在这里，我们引入了一种新的包含节点丢失的复制-分化模型。这种机制导致网络中孤立蛋白质的比例可以取严格介于0和1之间的值。为了理解这个新模型，我们对有节点丢失和无节点丢失的复制-分化模型的网络进行强攻击和弱攻击，并将结果与对两个真实的PPI网络（分别是……和……）进行类似攻击时获得的结果进行比较。我们发现，新模型更紧密地反映了PPI网络中强攻击和弱攻击所造成的损害。
