| Autor: |
Gomes, Juliana Carneiro, Masood, Aras Ismael, Silva, Leandro Honorato de S., da Cruz Ferreira, Janderson Romário B., Freire Júnior, Agostinho Antônio, Rocha, Allana Laís dos Santos, de Oliveira, Letícia Castro Portela, da Silva, Nathália Regina Cauás, Fernandes, Bruno José Torres, dos Santos, Wellington Pinheiro |
| Předmět: |
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| Zdroj: |
Scientific Reports; 6/2/2021, Vol. 11 Issue 1, p1-28, 28p |
| Abstrakt: |
The Covid-19 pandemic, a disease transmitted by the SARS-CoV-2 virus, has already caused the infection of more than 120 million people, of which 70 million have been recovered, while 3 million people have died. The high speed of infection has led to the rapid depletion of public health resources in most countries. RT-PCR is Covid-19's reference diagnostic method. In this work we propose a new technique for representing DNA sequences: they are divided into smaller sequences with overlap in a pseudo-convolutional approach and represented by co-occurrence matrices. This technique eliminates multiple sequence alignment. Through the proposed method, it is possible to identify virus sequences from a large database: 347,363 virus DNA sequences from 24 virus families and SARS-CoV-2. When comparing SARS-CoV-2 with virus families with similar symptoms, we obtained 0.97 ± 0.03 for sensitivity and 0.9919 ± 0.0005 for specificity with MLP classifier and 30% overlap. When SARS-CoV-2 is compared to other coronaviruses and healthy human DNA sequences, we obtained 0.99 ± 0.01 for sensitivity and 0.9986 ± 0.0002 for specificity with MLP and 50% overlap. Therefore, the molecular diagnosis of Covid-19 can be optimized by combining RT-PCR and our pseudo-convolutional method to identify DNA sequences for SARS-CoV-2 with greater specificity and sensitivity. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
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