Identifying essential proteins in dynamic protein networks based on an improved h-index algorithm

Abstract

Background: The essential proteins in protein networks play an important role in complex cellular functions and in protein evolution. Therefore, the identification of essential proteins in a network can help to explain the structure, function, and dynamics of basic cellular networks. The existing dynamic protein networks regard the protein components as the same at all time points; however, the role of proteins can vary over time. Methods: To improve the accuracy of identifying essential proteins, an improved h-index algorithm based on the attenuation coefficient method is proposed in this paper. This method incorporates previously neglected node information to improve the accuracy of the essential protein search. Based on choosing the appropriate attenuation coefficient, the values, such as monotonicity, SN, SP, PPV and NPV of different essential protein search algorithms are tested. Results: The experimental results show that, the algorithm proposed in this paper can ensure the accuracy of the found proteins while identifying more essential proteins. Conclusions: The described experiments show that this method is more effective than other similar methods in identifying essential proteins in dynamic protein networks. This study can better explain the mechanism of life activities and provide theoretical basis for the research and development of targeted drugs.