Evaluation of COVID-۱۹ mutations and predicting the rate of disease transmission and pathogenicity based on the types of mutations

Researchers have developed a new method that uses Artificial Intelligence to foresee the most likelymutations of pathogens like SARS-COV-۲, the virus that causes COVID-۱۹. SARS-CoV-۲, a novelcoronavirus mostly known as COVID-۱۹ has created a global pandemic. The world is now immobilized bythis infectious RNA virus. As of Jan ۵, already more than ۳.۱۵M people have been infected and ۵.۷۳M peopledied RNA viruses are different than DNA-based viruses in the sense that they have higher mutation rates,and hence, they have higher adaptive capacity. This mutation causes continuous evolution that leads to hostimmunity and therefore, based on the type of mutation, it affects the rate of disease transmission andpathogenicity This RNA virus can do the mutation in the human body. Accurate determination of mutationrates is essential to comprehend the evolution of this virus and to determine the risk of emergent infectiousdisease. The collected dataset is processed to determine the mutation of different parts of the Covid-۱۹separatelyWe proposed a model for the Virus Mutations Prediction. The proposed approach consists of four mainphases:۱. Sequences of datasets are preprocessed.۲. Once we have preprocessed sequences of data, they are transformed into a format that is suitable fortraining an LSTM network. In this case, a one-hot encoding of the integer values is used where each value isrepresented by a binary vector that is all “۰” values except for the pointer to the word, which is set to ۱۳. The input data are prepared to train on the LSTM encoder. After that, it is the role of the decoder totake the output from the encoder as integers and transform it into sequences۴. The obtained results are evaluated.

کلیدواژه ها:

Artificial Intelligence ، LSTM Algorithm ، COVID-۱۹ ، RNA viruses