Method for identifying controllable gene based on complex network structure

A technology of network structure and identification method, applied in the field of bioinformatics, which can solve the problems of information limitation, ignoring the interaction of neighbor nodes of nodes, complex network incompatibility, etc.

Active Publication Date: 2019-11-26
XIAN UNIV OF TECH
View PDF5 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

These methods have certain effectiveness in different networks, but the information considered is relatively limited, ignoring the interaction between the neighbor nodes of the node, so it is not suitable for complex networks to a large extent.

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Method for identifying controllable gene based on complex network structure
  • Method for identifying controllable gene based on complex network structure
  • Method for identifying controllable gene based on complex network structure

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0083] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0084] A controllable gene identification method based on complex network structure, such as Figure 5 shown, including the following steps:

[0085] Step 1: Reading data from tissue-specific regulatory networks

[0086] Each row in the original data contains two columns of data, representing the regulated gene and the regulated gene respectively;

[0087] Step 2: Classify the nodes in the network using four different node classification methods

[0088] The first is a node classification method based on controllability;

[0089] The second is a node classification method based on control capability;

[0090] The third is the node classification method based on the source of the control function;

[0091] The fourth is a node classification method based on the robustness of control edges;

[0092] Step 3: Combine the four classification...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention provides a method for identifying controllable gene based on complex network structure. A controllability node classification framework is constructed; genes are divided into different types for controlling role differences; a new gene is identified through statistical significance. According to the gene recognition method based on the controllable node classification framework, global information in a network is considered, gene classification is achieved from multiple control levels, the framework is applied to a tissue-specific regulation and control network, genes with remarkable biological significance can be systematically detected, and a tool platform is provided for further gene research.

Description

technical field [0001] The invention belongs to the field of bioinformatics and relates to a controllable gene identification method based on a complex network structure. Background technique [0002] Genes are internal factors that determine the appearance of organisms and have important biological significance. There are two approaches to the identification of these biologically significant genes. The first method is experimental technology, such as gene knockout technology, by inactivating the function of a specific gene, observing whether the life activities of the organism are abnormal, and then inferring the biological function of the gene. Experimental techniques are expensive, time-consuming, and not applicable to all organisms. The second approach is a bioinformatics computational approach that analyzes the importance of genes through computational methods based on biological networks. Computational methods are more efficient and less expensive than experimental ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G16B20/00
CPCG16B20/00
Inventor 金海燕曹甜王炳波王婉宁
Owner XIAN UNIV OF TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products