A method for identifying key proteins using a Drosophila optimization algorithm

Abstract

The invention discloses a method for identifying key proteins using a fruit fly optimization algorithm, transforming a protein interaction network into an undirected graph, constructing a dynamic protein interaction network, preprocessing edges and nodes of the dynamic protein interaction network, and randomly initializing The position of the fruit fly population, use the sense of smell to search for the random direction and distance of food, calculate the judgment value of the individual fruit fly odor concentration, calculate the odor concentration value of the fruit fly individual, find out the highest odor concentration value in the current population, use vision to fly to the food, Produce key proteins. The present invention can accurately identify key proteins; the results of simulation experiments show that the present invention performs well in indicators such as sensitivity, specificity, positive predictive value, negative predictive value, precision rate and recall rate harmonic value, and precise value; compared with other identification Compared with the method for key proteins, the method for identifying key proteins using the fruit fly optimization algorithm in the present invention 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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