Research On Post-translational Phosphorylation Modification Network Of Protein Based On Improved Probability Incremental Learning Algorithm

In recent years,with the continuous development of post-genome programs,proteomics has become an important part in the field of bioinformatics research.Among them,the protein structure and function of the regulatory role of protein post-translational modification,but also become a recent hot spot.Proteins are involved in the regulation of proteins,such as ubiquitination,phosphorylation,methylation,and other proteins,which are indispensable and important factors due to protein activity regulation,protein interaction,subcellular level localization and so on.As an important way to regulate protein function and structure,protein post-translational modification plays a vital role in the process of life.Once in the modification process abnormal,it is easy to cause different degrees of disease.To cardiovascular disease,for example,in the early stages of the vascular endothelial injury process,the relevant protein at different sites of phosphorylation,ubiquitination and other modifications is the direct cause of cardiovascular disease.Among them,as the most common in the human body is a modification,is the most extensive study of a modification,phosphorylation modification exists almost in the life of the various processes.The experimental data from this study are derived from the use of MALDI-TOF-TOF,LTQ Orbitrap and LCMS-IT-TOF high-resolution mass spectrometers for the treatment of vascular endothelial cells by the major pathogenic gene ox-LDL of atherosclerosis.The phosphorylation of the protein was studied by combining the time-series data of the control group and the peroxidation injury experimental group at different time points with the combination of nano-2D-HPLC and high-resolution mass spectrometry.The phosphorylation concentration of each protein site.The DAG-> PKC-> Ras in the MAPK signaling pathway and Ras-> MEK-> Src-> AR in Endocrinology / Hormones signaling pathways were screened by the KEGG signal path database,were involved in the construction of phosphorylation pathway.Based on the population-based incremental learning algorithm(PBIL),this paper introduces the Particle Swarm Optimization(PSO)algorithm to study the post-translational phosphorylation of protein by a new algorithm based on improved probabilistic enhancementThe According to the dynamic characteristics of phosphorylation after protein translation,the improved probabilistic enhancement learning algorithm combined with PBIL and PSO algorithm is used to construct the network model,and then the PSO algorithm is used to optimize the whole model of the model.accurate.Due to the dynamics and complexity of the phosphorylation network after protein translation,the network model chosen in this paper is a differential equation model.The general kinetic description of the phosphorylation process after protein translation is proposed,and the reverse engineering principle is used to obtain the power The relationship between phosphorylation of translational proteins between different protein sites was quantitatively described.In this paper,an improved probabilistic enhancement algorithm was used to construct a post-translational phosphorylation network for protein translation.Good results were obtained,which provided a new solution for the construction of post-translational phosphate phosphorylation network.It also revealed that the post-translational modification of protein Complex regulation and regulation,the pathogenesis of cardiovascular disease related to protein translation after the study of interactive regulation,as well as the treatment of cardiovascular disease in the process of action mechanism and the role of target research provides a new way of thinking.