Method for identifying key proteins based on cuckoo search algorithm

Abstract

The invention discloses a method for identifying key proteins based on a cuckoo search algorithm, and belongs to the technical field of biological information. A protein interaction network is converted into an undirected graph, denoising processing is conducted on the protein interaction network to acquire gene expression data, subcellular localization information, standard protein complex information and GO annotation information corresponding to the protein, weighting processing is conducted on edges and nodes of the purified protein interaction network to generate a bird nest and cuckoos and update a bird nest adaptive value to generate the key proteins. The method can accurately identify the key proteins; simulation results show that the indexes such as sensitivity, specificity, F measure, a positive predictive value, a negative predictive value, correct rate and the like are superior; compared with other existing identification methods, the optimizing characteristics of the cuckoo search algorithm and topological characteristics of the protein interaction network are combined to identify the key proteins, and the recognition accuracy of the key proteins is improved.

Description

technical field [0001] The invention belongs to the technical field of biological information, and in particular relates to a method for identifying key proteins based on a cuckoo search algorithm. Background technique [0002] Protein is the product of gene expression and the basic unit of substance and function of organisms. Protein plays an extremely important role in the life activities of cells and organisms. The importance of different proteins is also different. According to the importance of proteins in organisms, these proteins can be divided into two categories: key proteins and non-key proteins. Key proteins refer to those proteins whose deletion will cause the loss of the function of related protein functional modules and lead to the failure of the normal life activities of organisms. Key proteins provide a perspective on the molecular mechanism of biological organisms at the system level, and have great application value for disease diagnosis and drug design. ...

AI Technical Summary

Problems solved by technology

[0008] Prediction of key proteins based on the network level and its application research has become a hot spot in the field of bioinformatics. Although the identification of key proteins has received more and more attention, due to the complexity of life activities and the differences between species There are many unfavorable factors such as variability, incompleteness and unreliability of protein interaction data, and the recognition accuracy is still low

Moreover, most methods only use a small number of parameters or features to analyze key proteins in isolation or piecemeal, and lack a global and overall grasp of the key protein nodes.

[0009] Based on the defects of the above-mentioned key protein identification methods, the reliability of the protein interaction network is mainly considered, only some characteristics are considered, and the correlation analysis between various topological parameters and biological data is ignored, and the accuracy of key protein identification is low.

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