Identifying Essential Proteins in Dynamic PPI Network with Improved FOA

IAENG Internaitonal journal of computer science

Linqiang Pan¹  Xiujuan Lei²  Siguo Wang² 

[1] 1. Key Laboratory of Image Information Processing andIntelligent Control of Education Ministry of ChinaSchool of AutomationHuazhong University of Science and TechnologyWuhan 430074, Hubei, China2. School of Electric and Information EngineeringZhengzhou University of Light IndustryZhengzhou 450002, Henan, China;School of Computer ScienceShaanxi Normal UniversityXian 710119,Shaanxi, China

关键词: essential proteins;    protein-protein interaction (PPI);    dynamic PPI networks;    subcellular localization data;    fruit fly optimization algorithm (FOA);   

DOI  :  10.15837/ijccc.2018.3.3285

学科分类：计算机科学（综合）

来源: International Association of Engineers

【 摘 要 】

Identification of essential proteins plays an important role for understanding the cellular life activity and development in postgenomic era. Identification of essential proteins from the protein-protein interaction (PPI) networks has become a hot topic in recent years. In this work, fruit fly optimization algorithm (FOA) is extended for identifying essential proteins, the extended algorithm is called EPFOA, which merges FOA with topological properties and biological information for essential proteins identification. The algorithm EPFOA has the advantage of identifying multiple essential proteins simultaneously rather than completely relying on ranking score identification individually. The performance of EPFOA is analyzed on dynamic PPI networks, which are constructed by combining the gene expression data. The experimental results demonstrate that EPFOA is more efficient in detecting essential proteins than the state-of-the-art essential proteins detection methods.

【 授权许可】

CC BY