Gene selection method and system based on adaptive gene interaction regularization elastic network model

Abstract

The invention discloses a gene selection method and system based on an adaptive gene interaction regularization elastic network model. The method includes: evaluating the importance of each measured gene based on the Wilcoxon rank sum test; Quantify and add adaptive penalty weights, and then delete noise genes to obtain eigengenes; introduce penalty weights into the least squares loss function to construct an adaptive elastic network model; construct the adjacency matrix of gene interaction network; construct genes based on adjacency matrix Interactive network penalty; combine the adaptive elastic network model and gene interaction network penalty to construct an adaptive gene interaction regularized elastic network model; solve the optimal solution of the regularized elastic network model based on the gradient descent algorithm, based on the optimal solution Select genes. The present invention can adaptively select important genes that are highly correlated with the generation of tumors, and remove redundant, irrelevant genes and noise genes.

Description

technical field [0001] The invention belongs to the technical field of biological information, and in particular relates to a gene selection method and system based on an adaptive gene interaction regularization elastic network model. Background technique [0002] Tumor has now become one of the major diseases threatening human life and health. According to the 2018 Global Cancer Statistics Report, the number of new cancer cases in the world will reach 18.1 million in 2018, and the number of deaths will reach 9.6 million, and the number of people diagnosed with cancer every year It is still rising rapidly, but the research on the treatment and prevention of cancer is not very comprehensive. With the application and development of a large number of gene chip technologies, human beings have been able to obtain the normal gene expression information of various tissues one after another. Genes are the key to accurate disease judgment and reliable diagnosis. At the same time, i...

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Problems solved by technology

[0011] Aiming at the problems of low estimation efficiency, insufficient consideration of gene interaction and relatively large task load existing in existing gene selection methods, the present invention proposes a gene selection method and system based on an adaptive gene interaction regularized elastic network model, which overcomes the The above defects can adaptively select important genes that are highly related to tumor generation, and remove redundant, irrelevant genes and noise genes

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