A Grouping Method of Group Lasso Characteristic Based on Network Analysis

Abstract

The invention discloses a method for clustering lasso cluster characteristics based on network analysis, which is mainly used for solving the clustering of related expressed genes in bioengineering and establishing a lasso cluster model by using the method. The method comprises the steps of firstly, dividing experimental data into a positive data set and a negative data set, and respectively establishing a weighting co-expression gene network (adjacent matrix) corresponding to the positive data set or the negative data set; secondly, determining important network modules respectively corresponding to a positive sample and a negative sample; thirdly, simplifying a positive sample network module by utilizing a negative sample network module according to the experiment background; finally, clustering the characteristics according to the simplified positive sample network module, and establishing a lasso cluster and a promotion model of the lasso cluster according to the clustering. According to the method disclosed by the invention, the characteristic clustering of the lasso cluster is successfully and organically combined with module selection of network analysis, the operation is easy, the clustering method can be applied to screening of related genes in liver regenerative cell proliferation, and the method has an important application value in simulating a cell proliferation process of complicated diseases such as liver cirrhosis and cancer and screening new drugs.

Description

technical field [0001] The invention belongs to the technical field of bioengineering, and mainly relates to bioinformatics and biodata mining, in particular to a group lasso feature grouping method based on network analysis. Background technique [0002] Bioengineering is based on the theory of biology (mainly genetics, cytology, and biochemistry), combined with modern engineering technologies such as machinery, electronic computers, and chemical engineering, and making full use of the latest achievements in molecular biology to consciously manipulate genetic material. It is an emerging technology that these modified engineering cell lines are cultivated to produce a large number of useful metabolites or exert their unique physiological functions through cell proliferation. Its wide range of uses is mainly used in medicine and health, food and light industry, agriculture, animal husbandry and fishery, energy and chemical industry, metallurgical industry, environmental prote...

AI Technical Summary

Problems solved by technology

From a biological point of view, it is easy to divide genes into groups according to the gene regulatory network, but it is difficult to detect gene pathways and construct regulatory networks for complex biological processes

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