Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Gene regulatory network constructing method based on dynamic Bayesian network

A gene regulation network, dynamic Bayesian technology, applied in the direction of gene model, can solve the problems of high complexity, poor reconstruction performance, poor practicability, etc., to achieve the effect of reducing complexity

Inactive Publication Date: 2011-04-13
HANGZHOU NORMAL UNIVERSITY
View PDF2 Cites 11 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] In order to overcome the disadvantages of high complexity, poor reconstruction performance and poor practicability of the gene regulation network construction method of the existing Bayesian network, the present invention provides a dynamic-based Gene regulation network construction method based on Bayesian network

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
  • Gene regulatory network constructing method based on dynamic Bayesian network
  • Gene regulatory network constructing method based on dynamic Bayesian network
  • Gene regulatory network constructing method based on dynamic Bayesian network

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0023] The present invention will be further described below in conjunction with the accompanying drawings.

[0024] refer to Figure 1 to Figure 3 , a method for constructing a gene regulation network based on a dynamic Bayesian network, comprising the following steps:

[0025] Step 1: Obtain time series data of gene expression;

[0026] Step 2: The time series data is discretized into several expression levels using the discretization method;

[0027] Step 3: Set the time delay of the gene regulatory network;

[0028] Step 4: Using the structure learning algorithm of the dynamic Bayesian network to derive the gene regulation network by using the maximum likelihood method; the specific process is as follows: first, by calling the inference algorithm of the Bayesian network to fill the data set, and the incomplete data The structural learning problem is transformed into a structural learning problem under complete data that is easier to solve. The maximum likelihood algorit...

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 relates to a gene regulatory network constructing method based on a dynamic Bayesian network. The method comprises the following steps: 1) the time series data of gene expression can be obtained; 2) the discretization method is adopted to discretize the time series data into a plurality of expression levels; 3) the time delay of the gene regulatory network is set; and 4) the structure learning algorithm of the dynamic Bayesian network is utilized and the maximum likelihood method is adopted to deduce the gene regulatory network. By adopting the gene regulatory network constructing method, the complexity can be reduced effectively, the reconstruction performance can be improved; and the method has high practicability.

Description

technical field [0001] The invention relates to the field of biotechnology, and relates to a method for constructing a gene regulation network. Background technique [0002] Exploring and discovering the regulatory relationship and interaction mechanism between genes is a research hotspot and frontier topic in life sciences, and inferring gene regulatory networks from gene expression data is one of its research directions. The gene regulatory network is a complex nonlinear system. From the perspective of modeling the interaction and connection between genes, it is a directed network composed of nodes (representing genes) and directed edges (representing regulatory effects and directions). picture. [0003] At present, there are mainly methods such as Boolean network, differential equation and Bayesian network for constructing gene regulatory network. These methods abstract the real regulatory network at different levels. Boolean networks are used to qualitatively study gen...

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
Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/12
Inventor 吴剑丙陈喆钱永生
Owner HANGZHOU NORMAL UNIVERSITY
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com