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Method, system and storage medium for predicting pathogenicity of genome single-site variation

A prediction method and single-site technology, applied in the field of bioinformatics, can solve the problems of high cost, low reliability, and low prediction accuracy, and achieve cost saving, patient privacy protection, high accuracy and reliability Effect

Active Publication Date: 2022-03-25
TSINGHUA UNIV
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Problems solved by technology

[0003] The purpose of the present invention is to provide a method, system and storage medium for predicting the pathogenicity of a genome single-site variation, so as to solve the problem of low accuracy, low reliability, and low cost of predicting the pathogenicity of a genome single-site variation in the prior art. expensive problem

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[0030] The technical solutions in the embodiments of the present invention will be described clearly and completely below with reference to the embodiments of the present invention and the accompanying drawings in the embodiments:

[0031] The method for predicting the pathogenicity of genome single-site variation provided by the present invention is based on the deep learning method, and the genome single-site variation data obtained by sequencing and the reference genome sequences of various species (also known as evolutionary conservation data) are used as training data. Medical diagnosis results are used as category labels, and the model obtained after training can calculate the data of various unit-point variations and predict the probability of causing genetic diseases according to different needs.

[0032] The model basis of the present invention is a mixture of convolutional neural networks and multilayer perceptrons. The purpose of the convolutional neural network is ...

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Abstract

The invention relates to the technical field of bioinformatics, and provides a method, a system and a storage medium for predicting the pathogenicity of a genome single point variation. Among them, the method includes: according to the variation position and variation situation of the single point of the genome, obtaining the variation data of the single point of the genome and the data of the assisted evolution conservation; performing preprocessing on the data of the variation of the single point of the genome and the data of the assisted evolution conservation to generate a matrix; loading the model, Input the matrix, and perform feature extraction through densely connected convolutional neural network, use multi-layer perceptron to combine feature data and perform calculations, and output prediction results. The invention can solve the problems of low accuracy, low reliability and high cost in the prediction of pathogenicity of genome single point variation in the prior art.

Description

technical field [0001] The invention relates to the technical field of bioinformatics, in particular to a method, a system and a storage medium for predicting the pathogenicity of a single site variation in a genome. Background technique [0002] With the development of biomedical technology, the quality of high-throughput sequencing has been continuously improved and the cost has been continuously reduced, which makes the application scope of genome sequencing in human precision medicine more and more widely, especially the diagnosis and treatment of potential disease risks of subjects through sequencing. Screening is a major research hotspot in precision medicine. At the same time, the rapid development of machine learning methods in recent years has led people to try to use machine learning to solve some problems in the medical field. However, limited by the lack of medical diagnostic data and the lack of understanding of the characteristics of genome sequences, there ha...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G16B20/30
CPCG16B30/10G16B40/00G16B50/30G06N20/00G16B20/30G06N3/045G06F18/214
Inventor 江瑞宋绍铭
Owner TSINGHUA UNIV