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Method for identifying key module or key node in biomolecular network

A biomolecular network and key module technology, applied in biological systems, evolutionary biology, biostatistics, etc., can solve the problems of lack of quantitative analysis of key modules or key nodes, ignoring influence, ignoring module network topology, etc.

Active Publication Date: 2016-09-21
王忠 +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

At present, researchers have carried out the identification of key modules, but these existing studies often ignore the topology of the module network, ignore the impact of the relationship between modules on key modules, and lack quantitative analysis of key modules or key nodes.

Method used

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  • Method for identifying key module or key node in biomolecular network
  • Method for identifying key module or key node in biomolecular network
  • Method for identifying key module or key node in biomolecular network

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0059] Example 1 Identification and verification of key modules

[0060] The protein interaction network of the cerebral ischemia mouse model was intervened by the components of Qingkailing ( figure 2 ; see Zhang Yingying, Identification and comparison of the main modules of the protein network of the Qingkailing multi-component intervention cerebral ischemia model [D], China Academy of Chinese Medical Sciences, 2014):

[0061] The protein interaction network of the cerebral ischemia model group (Vehicle group) ( figure 2 a-1), consisting of 3750 nodes and 9162 edges;

[0062] The protein interaction network of the baicalin group (BA group) ( figure 2 b-1), is the protein interaction network after the drug baicalin intervenes in the cerebral ischemia model, consisting of 2813 nodes and 6217 edges;

[0063] The protein interaction network of the geniposide group (JA group) ( figure 2 c-1), is the protein interaction network after the drug geniposide intervenes in the...

Embodiment 2

[0078] Example 2 Identification and verification of key modules

[0079] For the three protein interaction networks (Vehicle group, BA group, and JA group) in Example 1, an unweighted modular interaction network was constructed in step 2 to identify key networks and pharmacological drivers.

[0080] The process is as follows.

[0081] Step 1, use the MCODE method to identify the modules of each network.

[0082] In step 2, an unweighted module interaction network is constructed based on the component dependencies between modules.

[0083] Step 3, select degree centrality, betweenness centrality and page level three measurement methods to identify key modules from a variety of methods for measuring the importance of nodes, wherein the key modules meet the following conditions to be determined as key modules: According to the The method of measuring the importance of nodes is calculated, and the obtained values ​​are arranged in descending order (A) ranks first in one metho...

Embodiment 3

[0093] Example 3 Identification and validation of key nodes, i.e. pharmacological drivers

[0094] Using the key module M of the geniposide group protein interaction network identified in Example 1 JA-1 , using degree centrality, betweenness centrality and page level three measurement methods to identify the key nodes in this key module, that is, pharmacological drivers, where the key nodes can be determined as key nodes only if they meet the following conditions: according to the importance of the measured nodes Calculated by the most accurate method, the obtained values ​​are arranged in descending order (A) ranks first in one method, (B) ranks in the top three in other methods.

[0095] The key module M in the protein interaction network of the geniposide group JA-1 It was found that the primary results of the three methods were consistent, all of which were Il6, see Table 8.

[0096] Table 8: Key module M of geniposide group JA-1 Identification results of key nodes i...

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Abstract

The invention provides a method for identifying a key module and a key node by fusing multiple methods based on a topological structure of a biomolecular complex network such as a protein interaction network, a gene expression regulation network, a biological metabolism network, an epigenetic network, a phenotype network or a signal conduction network. The method comprises the following main steps of performing module division on the network based on the biomolecular network, and comprehensively and quantitatively identifying the key module and the key node from multiple angles by adopting multiple measurement methods based on the topological structure of the network for the network or each module.

Description

technical field [0001] The invention belongs to the technical field of biological information. Specifically, the present invention relates to identification methods of key modules or key nodes in complex molecular networks of diseases and drug interventions, such as protein interaction networks, gene expression regulation networks, drug metabolism and drug targets, and other networks. Background technique [0002] With the advent of the era of omics and the development of high-throughput technologies, massive biological data sets have been generated, and common biomolecular networks have emerged, such as protein interaction networks, gene expression regulation networks, and drug metabolism networks. Effective analysis of these data networks can reveal mechanisms such as gene expression regulation, protein interaction, and metabolite interaction, which can then be applied to disease mechanism research and treatment, drug development, and other fields. [0003] Evidence shows...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F19/12G16B5/00
CPCG16B5/00G16B10/00G16B45/00G16B20/00G16B40/20
Inventor 张莹莹王忠王永炎
Owner 王忠
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