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

microRNA target position point prediction method based on support vector machine

A technology of support vector machines and target sites, which is used in the determination/inspection of microorganisms, biochemical equipment and methods, special data processing applications, etc.

Inactive Publication Date: 2011-07-20
ZHEJIANG UNIV
View PDF0 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In recent years, with the deepening of animal miRNA research, it has been found that, in addition to the target site region that directly interacts with miRNA, the flanking sequence of the target site, the position of the target site on the 3'UTR and other characteristics are also related to miRNA and miRNA. The binding of target sites is closely related [20-21], and these are not considered by previous prediction methods

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
  • microRNA target position point prediction method based on support vector machine
  • microRNA target position point prediction method based on support vector machine
  • microRNA target position point prediction method based on support vector machine

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0061] The method for the microRNA target site prediction based on support vector machine, comprises the steps:

[0062] 1. Establishment of training data set

[0063] Since the training set data is very important for machine learning methods, selecting appropriate positive and negative sample sets is one of the key points and difficulties of this study. Using the miRecords database, miRecordsversion 1[9] has a total of 1979 records, including 121 records for fruit flies and 1311 records for humans; only the data of these two animals are taken as data sets. After removing duplicate records and records with incomplete information (mainly because the position of the binding site is not given), a total of 278 miRNA-target site interaction pairs were obtained, of which 83 were from Drosophila and 195 were from human , these samples are used as positive samples.

[0064] Negative samples are often more important than positive samples for the specificity of a classifier. Previous...

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 discloses a microRNA target position point prediction method based on a support vector machine, comprising the following steps: 1) building a training data set comprising 278 positive samples and 194 negative samples; 2) building a characteristic set: the sample of each characteristic set is represented by one characteristic vector which contains each aspect information of the miRNA-target position point regulation pair and is divided into six parts, i.e. 128 characteristics; 3) selecting a simplified characteristic set: using a series of characteristic selection algorithms in Weka3 to screen 64 characteristics; 4) result evaluation: comparing the classifying capability of classifiers based on the characteristic set, the simplified characteristic set and the miTarget characteristic set; and 5) function annotation of an miRNA target gene. The invention has the meaning of building a characteristic which is found to be relative with miRNA target position point combination in recent years and developing a set of new miRNA target position point prediction methods; the predictor is optimized by the means of characteristic selection; the detection result comparison shows that the new adopted characteristic can help to predict the miRNA target position point.

Description

technical field [0001] The invention relates to a method for predicting a microRNA target site based on a support vector machine. Background technique [0002] microRNA (miRNA) is a single-stranded non-coding RNA with a length of about 22nt. Because microRNA plays a very important role in the post-transcriptional regulation of gene expression, miRNA has been widely concerned since its discovery. Studies have shown that miRNA has a very important impact on the growth and development of organisms. It is now generally believed that miRNAs achieve their negative regulatory functions by combining complementary to the mRNAs of their target genes, reducing the stability of mRNAs or inhibiting the translation of mRNAs. [0003] Since miRNA plays a pivotal role in many life processes of organisms, the study of miRNA function has been paid more and more attention. So far, more than 8,000 miRNAs have been discovered and recorded in the miRNA database miRBase[1-3], and this number is...

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 Patents(China)
IPC IPC(8): G06F19/22C12Q1/68
Inventor 陈铭何志嵩王匡宇白琳
Owner ZHEJIANG UNIV
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