Gene trait identification method based on torch supervised deep learning

A deep learning and genetic trait technology, applied in the field of biological information, can solve the problems of inability to classify and self-identify, and achieve the effect of convenient classification of corresponding traits and intelligent classification of corresponding traits

Active Publication Date: 2018-08-17
MELUX TECH CO LTD
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Problems solved by technology

However, BLAST also has certain limitations. It cannot perform gene classification and self-identification according to corresponding traits under deep learning, and it is powerless to intelligently classify corresponding traits and self-identify for large-scale genetic data sets.

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  • Gene trait identification method based on torch supervised deep learning
  • Gene trait identification method based on torch supervised deep learning
  • Gene trait identification method based on torch supervised deep learning

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Embodiment Construction

[0023] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments, wherein the schematic embodiments and descriptions are only used to explain the present invention, but are not intended to limit the present invention.

[0024] Such as Figure 1-Figure 7 As shown, the genetic trait identification method based on Torch supervised deep learning described in this specific embodiment, it adopts the following technical scheme:

[0025] Step 1: Preprocessing of gene PNG image information data to conform to the Tensor data object used for Torch deep learning model training;

[0026] Step 2: Use Torch to build a deep learning model, train the Tensor training data in the deep convolutional neural network model, and output the label vector and weight parameters after obtaining the ideal training data recognition results;

[0027] Step 3: After the model is successfully trained, the weight parameters between all the con...

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Abstract

The invention relates to the technical field of biological information, in particular to a method for identifying gene characters on the basis of Torch supervised deep learning. The technical scheme includes that the method comprises steps of firstly, preprocessing gene PNG (portable network graphic) image information data to enable the gene PNG image information data to conform to Tensor data objects for Torch deep learning model training; secondly, building deep learning models by the aid of Torch, training Tensor training data in deep convolutional neural network models to obtain perfect training data identification results and then outputting tag vectors and weight parameters; thirdly, extracting weight parameters of various connections of a certain category of result tags after all training is completed and inversely coding gene image data information to obtain related SNP (single nucleotide polymorphism) loci of characters corresponding to genes and corresponding weight parameters. The method has the advantages that the characters corresponding to the genes can be conveniently and intelligently classified by the aid of the method, genes with unknown characters can be subjected to self-identification, and the like.

Description

【Technical field】 [0001] The invention relates to the technical field of biological information, in particular to a gene trait identification method based on Torch supervised deep learning. 【Background technique】 [0002] The Human Genome Project laid the foundation for studying diseases from genes, and people hope to find the relationship between human diseases and genes. The basic principle of Genome-Wide Association Study (GWAS, Genome-Wide Association Study) is to select a certain statistical number of samples from the case group and the control group in the same population, and compare the SNP loci in the case group and the control group within the whole genome. If the frequency of a certain SNP site in the case group is significantly higher or lower than that in the control group, it is considered that the SNP site is associated with complex diseases. Although GWAS has discovered many SNPs associated with complex diseases, there are still many problems in GWAS, and th...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F19/12G06F19/24
CPCG16B5/00G16B40/00
Inventor 尹勰谢清禄余孟春
Owner MELUX TECH CO LTD
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