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

Method for predicting potential lncRNA disease based on random walk target convergence set technology

A random walk and technology prediction technology, applied in the field of bioinformatics, can solve problems such as undiscovered correlation, time complexity, and high cost

Active Publication Date: 2020-04-03
CHANGSHA UNIVERSITY +1
View PDF3 Cites 5 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, due to the high cost and time complexity of traditional biological experiments, the association of most long non-coding RNAs with diseases has not been discovered

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 predicting potential lncRNA disease based on random walk target convergence set technology
  • Method for predicting potential lncRNA disease based on random walk target convergence set technology
  • Method for predicting potential lncRNA disease based on random walk target convergence set technology

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0062] For many years, it was thought that an organism's genetic information was stored only in the genes used to code for proteins, and RNA had been considered an intermediary in the process by which DNA codes for proteins. However, recent studies have shown that protein-coding genes account for only a small portion of the human genome (less than 2%), and more than 98% of the human genome is not composed of gene-coded proteins and long non-coding RNAs. Furthermore, as the complexity of biological organisms increases, so does the importance of non-coding RNAs in biological processes. Generally speaking, according to the length of nucleotides in the transcription process, non-coding RNAs can be divided into two categories: short-chain non-coding RNAs and long-chain non-coding RNAs, in which short-chain non-coding RNAs consist of less than 200 nucleotides, Including microRNAs and transfer RNA, etc. However, long noncoding RNAs contain more than 200 nucleotides. In 1990, resear...

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 predicting a potential lncRNA disease based on a random walk target convergence set technology. The method comprises the following steps of: combining known long-non-coding RNA-disease association with long-non-coding RNA comprehensive similarity and disease comprehensive similarity to construct a heterogeneous network, so that the defect that a walking processcannot be started by adopting a traditional method based on RWR under the condition that no known long-non-coding RNA-disease association exists is overcome. Then, each node in the heterogeneous network establishes own TCS according to the network distance information, so that the particularity of different nodes in the walking process can be reflected, the prediction is more accurate, and the consumed time is less. Furthermore, by considering that for a given random walker, when the TCS has reached the final convergence state, some nodes may still not be included in the TCS, but are actuallyassociated with the TCS, and it is ensured that the prediction result is not missed.

Description

technical field [0001] The invention belongs to the field of bioinformatics, and specifically relates to a method for predicting the potential association between long-chain non-coding RNA and diseases. Background technique [0002] In recent years, long-non-coding RNAs (long-non-coding RNAs) have been proven to be closely related to the occurrence and development of many diseases that seriously endanger human health. However, due to the high cost and time complexity of traditional biological experiments, the association of most long non-coding RNAs with diseases has not been discovered. Therefore, it is urgent and necessary to establish efficient and reasonable computational models to predict the potential association between long non-coding RNAs and diseases. Contents of the invention [0003] In order to solve the above problems, the present invention provides a method for predicting potential lncRNA diseases based on random walk target convergent set technology that c...

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): G16B20/00G16B30/10G16B40/00
CPCG16B20/00G16B30/10G16B40/00Y02A90/10
Inventor 王雷邹赛李介臣陈治平
Owner CHANGSHA 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