Method for identifying key protein through fruit fly optimization algorithm

Abstract

The invention discloses a method for identifying key protein through a fruit fly optimization algorithm. The method includes the steps that a protein-protein interaction network is converted into an undirected graph, a dynamic protein-protein interaction network is constructed, the edges and nodes of the dynamic protein-protein interaction network are preprocessed, the position of a fruit fly group is randomly initialized, the food random direction and distance are searched for with the sense of smell, the taste concentration judgment value of each fruit fly individual is calculated, the odorconcentration value of each fruit fly individual is calculated, the highest odor concentration value in the current group is worked out, the fruit flies fly to the food with the sense of sight, and key protein is generated. By means of the method, the key protein can be accurately identified; the simulation experiment result shows that the method has good performance indexes including sensitivity,specificity, positive predictive value, negative predictive value, accuracy rate and recall rate harmonic value, precise value and the like; compared with other methods for identifying key protein, the method adopting the fruit fly optimization algorithm for identifying the key protein has certain advantages.

Description

technical field [0001] The invention belongs to the technical field of biological information, and relates to a method for identifying key proteins in a dynamic protein interaction network, in particular to a method for identifying key proteins using a fruit fly optimization algorithm. Background technique [0002] Proteins play an important role in the cells of basically every organism, key proteins are essential for the growth and development of an organism, and the absence of key proteins can render an organism lethal or unable to survive. Some recent research results show that the comprehensive analysis of key proteins can provide a deep understanding of the relationship between gene mutations and human diseases, and reveal the general principles of human diseases. Therefore, identifying key proteins is closely related to disease prediction and drug design. [0003] With the development of high-throughput technologies such as yeast two-hybrid, tandem affinity purificati...

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Problems solved by technology

[0007] Based on the above analysis, in the process of identifying key proteins, not only the topological characteristics of the network, including modularity, but also the timing and biological characteristics of the protein interaction network must be considered. However, in the existing identification methods, few There is a method that can meet the recognition accuracy and recognition efficiency of key proteins at the same time

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