标题： 蛋白质超网络：蛋白质网络中交互依赖性和扰动效应的逻辑框架 显示英文标题

标题： Protein Hypernetworks: a Logic Framework for Interaction Dependencies and Perturbation Effects in Protein Networks

摘要： 动机：蛋白质相互作用是构成细胞功能基础生化反应系统的基本构建模块。这种系统的复杂性和功能不是来自蛋白质相互作用本身，而是来自这些相互作用之间的依赖关系。因此，需要一种全面的方法来整合和利用有关这些依赖关系的信息。 结果：我们提出了一种方法，使用命题逻辑为蛋白质网络赋予相互作用依赖性，从而得到蛋白质超网络。 首先，我们展示了这个框架如何直接提高蛋白质复合物的预测效果。 接下来，我们表明在超网络中建模蛋白质扰动，而不是在网络中建模，可以更好地推断酵母中蛋白质的功能必要性。 此外，超网络提高了酵母中合成致死相互作用的预测效果，表明它们能够捕捉蛋白质之间的高阶功能关系。 结论：蛋白质超网络是建模蛋白质网络内蛋白质相互作用之间依赖关系的一致形式框架。 对酵母相互作用组的蛋白质超网络的初步应用表明了它们在推断复杂生化系统功能特征方面的价值。 显示英文摘要

摘要： Motivation: Protein interactions are fundamental building blocks of biochemical reaction systems underlying cellular functions. The complexity and functionality of such systems emerge not from the protein interactions themselves but from the dependencies between these interactions. Therefore, a comprehensive approach for integrating and using information about such dependencies is required. Results: We present an approach for endowing protein networks with interaction dependencies using propositional logic, thereby obtaining protein hypernetworks. First we demonstrate how this framework straightforwardly improves the prediction of protein complexes. Next we show that modeling protein perturbations in hypernetworks, rather than in networks, allows to better infer the functional necessity of proteins for yeast. Furthermore, hypernetworks improve the prediction of synthetic lethal interactions in yeast, indicating their capability to capture high-order functional relations between proteins. Conclusion: Protein hypernetworks are a consistent formal framework for modeling dependencies between protein interactions within protein networks. First applications of protein hypernetworks on the yeast interactome indicate their value for inferring functional features of complex biochemical systems.