Establishment method of gene regulating network based on two-way XGBoost

Abstract

The invention discloses an establishment method of a gene regulating network based on two-way XGBoost. Aiming at the characteristics of time sequence gene expression data, the relationship between anexpression value of a t moment gene and the positions before and after other gene t moment points is analyzed, and local-in and local-out two-way models are established; in a single model, establishment of the gene regulating network is divided into multiple regression equations, the condition of high-order time lag is fully considered, weights of characteristics in a single regression equation are evaluated through the XGBoost, and finally a rank of regulating relationships is acquired; normalization residuals are adopted for carrying out secondary weighting on the characteristics in each independent regression equation, and the weights of the two-way models for the same pair of regulating relationships are combined to form a value to serve as the final score of each pair of gene regulating relationships. The method is suitable for establishing different scales of gene regulating networks under the time sequence gene expression data, and the accuracy of network deduction can be effectively improved.

Description

technical field [0001] The invention relates to the field of bioinformatics, and relates to a method for constructing complex biological networks. Background technique [0002] The life activities of organisms are based on the interaction of a large number of biomolecules, including the signal transduction between cells, the interaction between proteins, and the mutual influence of genes. Many complex connections can be abstractly expressed in the form of biological networks. Among many biological networks, gene regulatory network represents a mechanism to control gene expression levels in organisms. According to the gene regulatory network, isolated studies of an isolated gene often cannot reflect its complex changes, and the expression level of a gene is affected by the expression content of other genes, including promotion and inhibition relationships. Gene regulation occurs in multiple stages such as biological transcription and translation, and is affected by specific ...

AI Technical Summary

Problems solved by technology

[0007] Although there are a large number of gene regulatory network construction methods, these methods are limited by the network scale and computational model, and there are still many deficiencies in construction ability and accuracy.

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