Coronavirus sequence recognition method based on gated recurrent unit neural network

Abstract

The invention relates to a coronavirus sequence recognition method based on a gated recurrent unit neural network. The coronavirus sequence recognition method comprises the following steps: S1, collecting data; S2, preprocessing the collected data, and performing data extraction from an original training sample to obtain a training set, a verification set and a test set; establishing an independent test set based on coronavirus sequences; S3, encoding each data set obtained in the S2, and establishing a classification model for training coronavirus sequences; S4, correcting the model; S5, counting an output score of the model to each sequence of a test set after the coronavirus sequence and the human genome sequence are merged; S6, setting a rejection interval according to the distributioncondition of the output score so as to reduce errors; S7, when the output score is larger than or equal to the upper limit threshold value of the rejection interval, judging the sequence to be a coronavirus sequence; and when the output score is less than or equal to the lower limit threshold of the rejection interval, judging that the sequence is a human genome sequence.

Description

technical field [0001] The present invention relates to the technical fields of neural network, data processing and computer simulation, and more specifically relates to a coronavirus sequence recognition method based on a gated recurrent unit neural network. Background technique [0002] Coronavirus (CoV) is a class of enveloped single-stranded positive-sense RNA viruses that cause a variety of diseases in mammals and birds. Some coronaviruses are highly contagious, pathogenic, and fatal in humans, and have a huge negative impact on national health, social stability, and national economic development. [0003] Real-time reverse transcription polymerase chain reaction (Real-time Reverse-transcription Polymerase Chain Reaction, RT-PCR) amplification method is the method of choice for the detection of coronaviruses. This method has the advantages of real-time monitoring, high sensitivity, and high specificity, but it also has some disadvantages, such as the inability to detec...

AI Technical Summary

Problems solved by technology

This is technically demanding, time-consuming and low-sensitivity

[0005] The traditional method of high-throughput sequencing data analysis is sequence alignment. Although there are many sequence alignment

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