A method for constructing regulatory networks of differentially expressed genes in specific cancers

A cancer differential expression and gene regulation network technology, applied in special data processing applications, instruments, calculations, etc., can solve the problems of reducing computational complexity, single data source, and high computational complexity, so as to reduce complexity and improve computational complexity. Precision, high-precision effect

Inactive Publication Date: 2018-05-22
JILIN UNIV
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Problems solved by technology

[0003] The present invention designs and develops a method for constructing a specific cancer differentially expressed gene regulatory network, which overcomes the defects of high computational complexity, single data source, and unsuitability for the construction of a genome-wide regulatory network in existing methods, and greatly reduces the computational complexity. and have higher precision

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  • A method for constructing regulatory networks of differentially expressed genes in specific cancers
  • A method for constructing regulatory networks of differentially expressed genes in specific cancers
  • A method for constructing regulatory networks of differentially expressed genes in specific cancers

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Embodiment Construction

[0038] The present invention will be further described in detail below in conjunction with the accompanying drawings, so that those skilled in the art can implement it with reference to the description.

[0039] Such as figure 1 As shown, the present invention provides a method for constructing a specific cancer differentially expressed gene regulatory network, and the specific steps are as follows:

[0040] Step 1 S110, construction of backbone gene interaction network.

[0041] The skeleton gene interaction network is a weighted network, in which the weight represents the functional similarity between genes, and the weight calculation method is as follows:

[0042]

[0043]Among them, m represents the number of types of gene-related information. In this method, m=3 is preferred, and only three aspects of information, namely gene ontology annotation information, gene metabolic pathway information, and known inter-gene interaction relations, are considered. Sim n (G i ,...

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Abstract

The invention discloses a construction method for a specific cancer differential expression gene regulation and control network.The method includes the following steps of firstly, constructing a framework gene interaction network according to function similarity weight numbers between genes; secondly, conducting module division on the framework gene interaction network through a segmenting method; thirdly, screening out differential expression genes through complete genome methylation data; fourthly, classifying the screened-out differential expression genes according to functions; fifthly, using all the differential expression genes mapped to each same function module as a function classification; sixthly, constructing the regulation and control network of all the genes in each function classification function; seventhly, conducting sub-network splicing under guidance of a framework network.The calculation complexity is greatly reduced, and high precision is achieved.

Description

technical field [0001] The invention relates to the technical field of gene regulation network, in particular to a method for constructing a specific cancer differentially expressed gene regulation network. Background technique [0002] Constructing a regulatory network of differentially expressed genes in a specific cancer is of great significance for identifying the pathogenic genes of this cancer and screening for drug targets. The current methods in the construction of gene regulatory networks are mainly divided into four categories: 1, methods based on similarity measurement; 2, methods based on graph structure search; 3, methods based on probabilistic reasoning; 4, methods based on equation solving. In the method based on similarity measurement, typical similarity measurement strategies include: Pearson correlation coefficient, mutual information, distance correlation, etc. For example, the ARACNE algorithm proposed by Margolin et al. is based on the method of mutual ...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F19/20
CPCG16B25/00
Inventor 刘桂霞苏令涛孟祥宇马青山
Owner JILIN UNIV
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