Cancer targeted marker mapping method based on coexpression network

Abstract

The invention discloses a cancer targeted marker mapping method based on a coexpression network. The method comprises the following steps: 1) building a coexpression basic network, according to gene expression data of a feature gene, calculating an adjacent matrix and a topology matrix; 2) extracting features of the coexpression basic network, namely converting each gene node of the topology network to a feature vector which is used as a feature value of the network; 3) training a neural network model, according to a migration sequence, executing the training of neutral network model parameters; and 4) executing the cancer targeted marker mapping, according to a clustering center self-adaptive algorithm based on a density peak, executing the automatic discovery of a targeted gene community. The provided method has the good universality and precision, and is capable of realizing the target gene mapping by using the building of the coexpression basic network, the extraction of the node feature vector and the automatic discovery of the gene community.

Description

technical field [0001] The invention belongs to the technical field of biological information, and in particular relates to a cancer targeting target gene mapping method. Background technique [0002] With the continuous improvement of science and technology and medical level in recent years, people's ability and confidence in fighting diseases have been continuously enhanced, but there are still many defects and technical obstacles. According to the cancer report of the World Health Organization, in the past five years, the number of cancer cases in China accounted for about one-fifth of the total number of global cases, and the number of deaths due to cancer has exceeded one-quarter of the total number of global cancer deaths. An important reason for the high mortality rate of cancer is that most cancers in my country are found in the middle and late stages. Therefore, while people continue to study new cancer treatment methods, more scientific research efforts need to be...

AI Technical Summary

Problems solved by technology

[0005] Aiming at the complexity of the co-expression network, the present invention constructs the basic network by calculating the correlation coefficient of the expression level between genes, uses second-order random walk and neural network model training to obtain the eigenvectors of the network nodes, and designs an adaptive algorithm for the clustering center Perform automated discovery of targeted gene communities

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