Gene regulation and control network re-building method based on cross-platform gene expression data

A technology of gene regulation network and gene expression, applied in electrical digital data processing, special data processing applications, instruments, etc., to avoid excessive smoothing of data, simple method, and poor comparability.

Active Publication Date: 2017-08-04
GUANGDONG UNIV OF TECH
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Problems solved by technology

Therefore, the causal graph model can well solve the problem of gene regulatory network reconstruction. In recent years, there have been many studies on gene regulatory network reconstruction

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  • Gene regulation and control network re-building method based on cross-platform gene expression data
  • Gene regulation and control network re-building method based on cross-platform gene expression data
  • Gene regulation and control network re-building method based on cross-platform gene expression data

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Embodiment Construction

[0034] The specific embodiment of the present invention will be further described below in conjunction with accompanying drawing:

[0035] Such as figure 1 As shown, a gene regulatory network reconstruction method based on cross-platform gene expression data, including the following steps:

[0036] S1), obtain the gene expression data from p sequencing platforms from the GEO gene expression database, wherein each sequencing platform includes multiple gene samples, preprocess the gene expression data of p sequencing platforms respectively, and delete the gene expression data in each sequencing platform Gene samples with too much missing gene expression, and the gene expression data of p sequencing platforms after preprocessing are combined to obtain a gene sample set X={x 1 ,x 2 ,...x m}, and then from the gene sample set X={x 1 ,x 2 ,...x m} from each gene sample to extract the expression of n genes to obtain the gene regulation network sample set G={g 11 , g 12 ,... g...

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Abstract

The invention relates to a gene regulation and control network re-building method based on cross-platform gene expression data. Gene expression data from p sequencing platforms is obtained and preprocessed according to the characteristics of the cross-platform gene expression data, n gene expression quantities are extracted from each gene sample, a father and son node sets of each gene expression quantity is obtained based on the mixed type condition independence testing of partial correlation coefficients, the father and son node sets are applied to the three processes of a learning network framework of cross-platform cause-effect network structure learning, v-structure determination and maximized direction marking, and a cross-platform gene regulation and control network is rebuilt. The problems of a cross-platform gene regulation and control network are solved through a cause-effect graph model, high-dimensional gene regulation and control network rebuilding can be directly and effectively carried out through the cross-platform gene expression data, data excess smoothness and other problems caused in the data preprocessing process are avoided, and the correctness rate and the recall rate of the rebuilding result of the cross-platform gene regulation and control network are increased.

Description

technical field [0001] The invention relates to the technical field of biological information processing, in particular to a gene regulation network reconstruction method based on cross-platform gene expression data. Background technique [0002] The gene regulatory network is a complex network that reflects the mutual influence relationship between genes. It plays a very important role in the study of the internal laws of life phenomena. It is a challenge in bioinformatics to use gene expression data to discover the gene regulatory relationship. With the rapid development of gene microarray technology, a variety of gene sequencing platforms have emerged. However, due to the different sequencing platforms and the differences in experimental environments, the gene expression data generated under different sequencing platforms often cannot be compared directly. , high-dimensional issues. Typical gene regulatory network reconstruction methods are mostly suitable for single-pla...

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Application Information

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IPC IPC(8): G06F19/20
Inventor 蔡瑞初林殷娴郝志峰温雯谢峰许柏炎陈薇陈炳丰
Owner GUANGDONG UNIV OF TECH
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