A Reliable Neighbor-Based Method for Identifying Essential Proteins by Integrating Gene Expressions, Orthology,and Subcellular Localization Information

摘要

Essential proteins are those necessary for the survival or reproduction of species and discovering such essential proteins is fundamental for understanding the minimal requirements for cellular life,which is also meaningful to the disease study and drug design.With the development of high-throughput techniques,a large number of Protein-Protein Interactions (PPIs) can be used to identify essential proteins at the network level.Up to now,though a series of network-based computational methods have been proposed,it is still a challenge to improve the prediction precision as the high false positives in PPI networks.In this paper,we propose a new method GOS to identify essential proteins by integrating the Gene expressions,Orthology,and Subcellular localization information.The gene expressions and subcellular localization information are used to determine whether a neighbor in the PPI network is reliable.Only reliable neighbors are considered when we analyze the topological characteristics of a protein in a PPI network.We also analyze the orthologous attributes of each protein to reflect its conservative features,and use a random walk model to integrate a protein's topological characteristics and its orthology.The experimental results on the yeast PPI network show that the proposed method GOS outperforms the ten existing methods DC,BC,CC,SC,EC,IC,NC,PeC,ION,and CSC.