Intelligent inference method for large-scale gene regulation and control network
A gene regulation network and large-scale technology, applied in the field of intelligent inference for large-scale gene regulation networks, can solve the problems of low computational efficiency and low accuracy, and achieve the effect of improving computational efficiency and accuracy
Pending Publication Date: 2021-10-15
DALIAN MARITIME UNIVERSITY
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[0004] The present invention provides a name to overcome technical problems such as low calculation efficiency and low accuracy
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[0043] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments It is a part of embodiments of the present invention, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.
[0044] This embodiment provides an intelligent inference method for large-scale gene regulatory networks, such as figure 1 , characterized by including:
[0045] Step 1. In the two-dimensional space of gene expression data point distribution, use m*n grid to divide the data space, so that the frequency of the data point falling in the (x, y)th gr...
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The invention discloses an intelligent inference method for a large-scale gene regulation and control network, which comprises the following steps: dividing a data space by using a grid in a two-dimensional space with gene expression data point distribution, taking the frequency of the data points falling in a grid cell as estimation of a joint probability distribution function, and determining mutual information between expression values of a gene x and a gene y; calculating mutual information in the grids with different sizes to obtain a maximum mutual information coefficient, and obtaining a key regulatory gene set of the target gene; calculating the importance of the regulatory gene to the target gene by using a key regulatory gene importance fusion algorithm to obtain an importance matrix; reserving the regulation and control relations with the control intensity exceeding a set threshold value in the importance matrix, and forming a gene regulation and control network by the regulation and control relations with the control intensity exceeding the set threshold value. According to the method, redundant gene expression information is eliminated aiming at the sparsity of key regulatory genes in a large-scale gene regulatory network, the calculation efficiency is effectively improved, and the accuracy of deducing the regulatory relation can be improved.
Description
technical field [0001] The invention relates to the field of gene regulation, in particular to an intelligent inference method for a large-scale gene regulation network. Background technique [0002] The gene regulatory network is a dynamic biochemical network formed by the interaction between genes. It can recognize and understand the transmission of biological genetic signals, cell division and other activity rules from a systematic perspective. Mechanisms are crucial. In addition, the gene regulatory network can analyze and identify the key regulatory genes of diseased cells, which is helpful for the diagnosis and treatment of complex diseases such as tumors and the development of targeted drugs. Therefore, inferring gene regulatory networks is an important research content of systems biology. With the development of high-throughput sequencing technology, researchers have obtained a large amount of biological gene expression data. For example, the Escherichia coli data ...
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Login to View More IPC IPC(8): G16B20/20
CPCG16B20/20Y02A90/10
Inventor 马宝山吴一铭宓东宁乔张萌
Owner DALIAN MARITIME UNIVERSITY