Method for quantitatively analyzing changes of modules in biological molecular networks before and after drug intervention

A biomolecular network and quantitative analysis technology, applied in the fields of biological systems, bioinformatics, special data processing applications, etc., can solve problems such as ignoring comprehensive quantitative analysis

Active Publication Date: 2017-03-15
王忠 +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] In previous studies, the measurement of the degree of module change was mostly quantitatively analyzed from one or several topologica

Method used

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  • Method for quantitatively analyzing changes of modules in biological molecular networks before and after drug intervention
  • Method for quantitatively analyzing changes of modules in biological molecular networks before and after drug intervention
  • Method for quantitatively analyzing changes of modules in biological molecular networks before and after drug intervention

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0050] Example 1 Intervention of mouse cerebral ischemia model with effective components of Qingkailing, quantification of changes in modules in protein interaction networks, and identification of effective change module pairs (fusion of 10 topological parameters)

[0051] Data Sources

[0052] The data in this example are derived from: the use of five effective components of refined Qingkailing, namely baicalin (BA), geniposide (JA), cholic acid (UA), baicalin + geniposide (BJ; BA+JA) , geniposide + cholic acid (JU; JA + UA) and the invalid component mother of pearl (CM) intervened in the mouse cerebral ischemia-reperfusion injury model, and the significantly differentially expressed genes were significantly differentially expressed by Ingenuity Pathway Analysis (IPA) Perform analysis to extract statistically significant gene sets associated with biological function annotations in IPA biological function enrichment results. Among them, the model group (Vehicle) contained 1...

Embodiment 2

[0083] Example 2 Intervention of mouse cerebral ischemia model with effective components of Qingkailing, quantification of changes in modules in protein interaction networks, and identification of effective change module pairs (8 topological parameters fusion)

[0084] Use the same network data as in Example 1. In this embodiment, Step 1 and Step 2 are the same as Embodiment 1.

[0085] Step 3, using 8 parameters, namely non-overlapping nodes, non-overlapping edges, overlapping nodes, overlapping edges, network density, network centrality, network average weight, shortest path, these 8 topological parameters representing different dimensions of the module are fused, and at the same time The weight of each parameter is shown in Table 8. Applying the k value method described in Example 1, the degree of change of the module from the disease state to the state of the JU group after drug intervention is expressed as follows:

[0086] Table 8 Each variable represents parameters ...

Embodiment 3

[0097] Example 3 Intervention of mouse cerebral ischemia model with effective components of Qingkailing, quantification of changes in modules in protein interaction networks, and identification of effective change module pairs (fusion of 5 topological parameters)

[0098] Use the same network data as in Example 1. In this embodiment, Step 1 and Step 2 are the same as Embodiment 1.

[0099] In step 3, 5 parameters are used, namely, non-overlapping nodes, non-overlapping edges, overlapping nodes, overlapping edges, and network centrality, which represent the topological parameters of different dimensions of the module, for fusion, and the weights of each parameter are shown in Table 11. Applying the k value method described in Example 1, the degree of change of the module from the disease state to the state of the BJ group after drug intervention is expressed as follows:

[0100] Table 11 Each variable represents parameters and weights (5 parameters)

[0101]

[0102] ...

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Abstract

The invention provides a quantitative analysis method used for quantifying and comparing change degrees of modules in biological molecular networks before and after drug intervention. According to the method, topological parameters of different dimensionalities (attributes) of the modules are integrated, an integrated comprehensive index for quantifying changes of the modules is established, and the change degrees of the modules in the biological molecular networks before and after drug intervention are quantitatively analyzed. The method includes the steps that firstly, the biological molecular networks before and after drug intervention are built respectively, and module recognition is conducted; secondly, the changed modules in biological molecular networks before and after drug intervention are matched, and a changed module pair is determined; thirdly, the topological parameters representing different dimensionalities of the modules are integrated, a module comprehensive evaluation system is built by means of weights of the topological parameters, and the change degree of overall conformation of the modules in the biological molecular networks before and after drug intervention is calculated. The method can be used in the fields of biological network analysis, new drug research, development and design, pharmacological mechanism research and the like.

Description

technical field [0001] The invention belongs to the technical field of biological information. Specifically, the present invention relates to the quantification of modules in complex biomolecular networks such as protein interaction networks, gene expression regulation networks, drug metabolism, and drug targets that change from one conformation to another after drug intervention method. Background technique [0002] Network structure analysis is the process of representing a system of interest as a network, and then using quantitative indicators to study the topology of the network. As a medium granularity of the network structure level, the module represents the local characteristics and network composition of the network. Therefore, the network topology parameter measurement method can be used to describe the topological characteristics of modules. [0003] Network pharmacology believes that when the biological system is in a state of homeostasis and equilibrium, the b...

Claims

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Application Information

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IPC IPC(8): G06F19/12G16B5/00
CPCG16B5/00
Inventor 王忠于亚南
Owner 王忠
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