An Iterative Model for Identifying Essential Proteins Based on the Whole Process Network of Protein Evolution

Zhang, Zhen1; Zhu, Yaocan2; Pei, Hongjing3; Wang, Xiangyi1; Wang, Lei1,2

2023

10.2174/1574893618666230315154807

CURRENT BIOINFORMATICS   影响因子和分区

1574-8936

2212-392X

Introduction Essential proteins play important roles in cell growth and regulation. However, due to the high costs and low efficiency of traditional biological experiments to identify essential proteins, in recent years, with the development of high-throughput technologies and bioinformatics, more and more computational models have been proposed to infer key proteins based on Protein-Protein Interaction (PPI) networks. Methods In this manuscript, a novel prediction model named MWPNPE (Model based on the Whole Process Network of Protein Evolution) was proposed, in which, a whole process network of protein evolution was constructed first based on known PPI data and gene expression data downloaded from benchmark databases. And then, considering that the interaction between proteins is a kind of dynamic process, a new measure was designed to estimate the relationships between proteins, based on which, an improved iterative algorithm was put forward to evaluate the importance of proteins. Results Finally, in order to verify the predictive performance of MWPNPE, we compared it with state-of-the-art representative computational methods, and experimental results demonstrated that the recognition accuracy of MWPNPE in the top 100, 200, and 300 candidate key proteins can reach 89, 166, and 233 respectively, which is significantly better than the predictive accuracies achieved by these competitive methods. Conclusion Hence, it can be seen that MWPNPE may be a useful tool for the development of key protein recognition in the future.

Essential protein recognition whole process network protein evolution computational methods entropy protein-protein interaction

SCI

英语

其他

Biochemistry & Molecular Biology ; Mathematical & Computational Biology

Biochemical Research Methods ; Mathematical & Computational Biology

WOS:001013555100007

BENTHAM SCIENCE PUBL LTD

Web of Science

1.Changsha Univ, Inst Bioinformat Complex Network Big Data, Changsha 410022, Peoples R China
2.Changsha Univ, Big Data Innovat & Entrepreneurship Educ Ctr Hunan, Changsha 410022, Peoples R China
3.Southern Univ Sci & Technol, Sch Med, Shenzhen 518055, Peoples R China

Zhang, Zhen,Zhu, Yaocan,Pei, Hongjing,et al. An Iterative Model for Identifying Essential Proteins Based on the Whole Process Network of Protein Evolution[J]. CURRENT BIOINFORMATICS,2023,18(4).

Zhang, Zhen,Zhu, Yaocan,Pei, Hongjing,Wang, Xiangyi,&Wang, Lei.(2023).An Iterative Model for Identifying Essential Proteins Based on the Whole Process Network of Protein Evolution.CURRENT BIOINFORMATICS,18(4).

Zhang, Zhen,et al."An Iterative Model for Identifying Essential Proteins Based on the Whole Process Network of Protein Evolution".CURRENT BIOINFORMATICS 18.4(2023).