Breast cancer occurrence related characteristic gene screening method

A screening method and related feature technology, applied in the field of bioinformatics, can solve the problems of missed selection of important genes, inability to fully retain characteristic genes, lack of effectiveness of complex collinearity processing, etc., and achieve the effect of high accuracy

Inactive Publication Date: 2018-02-23
BEIJING UNIV OF TECH
View PDF0 Cites 6 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The above eigengene screening methods are not effective for multicollinearity between features, and cannot fully retain eigengenes with the same biological function, which may easily cause important genes to be missed, and some methods cannot be independent of the classification model. It is greatly affected by the performance of the classifier

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
  • Breast cancer occurrence related characteristic gene screening method
  • Breast cancer occurrence related characteristic gene screening method
  • Breast cancer occurrence related characteristic gene screening method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0014] Such as figure 1 As shown, the present invention provides a method for screening characteristic genes related to breast cancer occurrence. Based on the breast cancer data in the TCGA cancer genomics database, multiple screening methods are used to screen the characteristic genes for cancer occurrence and used for classification by classification models.

[0015] Preferably, the multiple screening method comprehensively performs multi-step screening on the whole genome by combining correlation screening, significant difference screening and elastic network screening.

[0016] Aspects of the method are described in detail below in conjunction with the data.

[0017] 1. Material selection and data processing

[0018] The present invention selects Illumina Infinium Human Methylation 450K, Illumina Infinium Human Methylation 27K two test platforms breast cancer methylation data and IlluminaHi Seq 2000RNA Sequencing Version 2 test platform gene expression data in the TCGA pu...

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 breast cancer occurrence related characteristic gene screening method. With breast cancer data in a TCGA database being a study object, a multi-characteristic gene screeningmethod is adopted, and a real characteristic gene is screened from the aspects of correlation, specificity, biological functions and the like. Based on cancer genomic data, through the characteristicgene extracting method, the gene related to early cancer occurrence is extracted, a classification model is built, and therefore early breast cancer automatic diagnosis is achieved.

Description

technical field [0001] The invention belongs to the field of bioinformatics, and relates to a method for screening characteristic genes related to breast cancer occurrence, which is used for identification and automatic diagnosis of characteristic genes related to cancer occurrence, and has high efficiency and universal applicability. Background technique [0002] The rapid development of high-throughput gene sequencing technology such as gene microarray technology and bioinformatics has provided a necessary means for large-scale screening of cancer-related genes from the genome level. However, the ultra-high-dimensional, high-noise, and small-sample characteristics of gene methylation microarray data make it easy for a few important gene information to be submerged in the noise of tens of thousands of genes in the whole genome, resulting in information saturation. cause difficulty. Therefore, the first task is to reduce the dimensionality of the data through feature select...

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): G06F19/18G06F19/24G06K9/62
CPCG16B20/00G16B40/00G06F18/2411
Inventor 李晓琴王学栋常宇
Owner BEIJING 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