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A method for constructing signal transduction network based on multivariate Granger test

A technology of signal transduction and network construction, applied in informatics, genomics, bioinformatics, etc., can solve problems such as inapplicability, and achieve the effect of improving accuracy

Active Publication Date: 2018-10-09
CENT SOUTH UNIV
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AI Technical Summary

Problems solved by technology

[0005] At present, although there are some models and methods for constructing directed biological networks, the accuracy of these models and methods for constructing biological networks needs to be further improved
In addition, due to the time slice characteristics of biological gene expression data, some traditional Granger test methods cannot be applied

Method used

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  • A method for constructing signal transduction network based on multivariate Granger test
  • A method for constructing signal transduction network based on multivariate Granger test
  • A method for constructing signal transduction network based on multivariate Granger test

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Experimental program
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Embodiment Construction

[0028] 1. Preprocessing of gene expression data

[0029] Read in the time series gene table data file with g i, t Represents the expression value of gene i at time t, and performs two-norm normalization under the time series expression group of this gene:

[0030]

[0031] M represents the normalized number of time slices of gene expression data x i, t It is used as the gene expression value in subsequent steps.

[0032] Second, construct the coefficient matrix

[0033] Based on the assumptions of time stationarity and the first-order Markov model, a linear regression equation is constructed:

[0034] x i, t =∑ 0 r j, t-1 x j, t-1 (2)

[0035] Where x j, t-1 Indicates the expression value of gene j at time t-1, r j, t-1 Represents the influence coefficient of the expression value on gene i at time t-1, and N represents the total number of genes. Obtain the matrix equation according to the linear equation:

[0036]

[0037] Where r i, j Indicates the influence coefficient of gene i...

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Abstract

The invention discloses a method for constructing a signaling transduction network based on a multivariate Granger test. The method comprises the following steps: performing 2-norm standardization on the input timing sequence gene expression data; respectively constructing 1-t-1 and 2-t timing sequence gene expression matrixes for gene expression data of t time slices after 2-norm standardization, establishing an order Markov-based linear equation, calculating to obtain a coefficient matrix and an expression value matrix through singular value decomposition, and calculating the residual Rss* according to the obtained coefficient matrix; disturbing timing sequence gene expression of each gene, calculating the disturbed residual, obtaining residual distribution Rss, sorting Rss* in Rss, and obtaining significance alpha of the coefficient. The method disclosed by the invention is applicable to the condition that real timing sequence gene expression data time slices are extremely few, and the accuracy of directed deduction is effectively improved.

Description

Technical field [0001] The invention relates to the field of bioinformatics, and relates to a method for constructing a complex biological network. Background technique [0002] In biological systems, common biological structures in the form of networks include gene transcription regulation networks, biological metabolism and signal transduction networks, and protein interaction networks. Among them, gene transcription regulation network, biological metabolism and signal transduction network all have transmission directionality. Gene regulatory network is a mechanism for controlling gene expression in organisms. Studies have shown that genes and gene products do not work alone, but participate in complex and interconnected pathways and networks. These genes interact and influence each other, resulting in the mechanism of cells, tissues, organs and organisms, forming a complex system like a "gene network" to promote evolution. The metabolic network is an abstract network compos...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F19/18
CPCG16B20/00
Inventor 李敏郑瑞清王建新
Owner CENT SOUTH UNIV
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