About: COVIDier: A Deep-learning Tool For Coronaviruses Genome And Virulence Proteins Classification

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An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
title	COVIDier: A Deep-learning Tool For Coronaviruses Genome And Virulence Proteins Classification
Creator	Alsamman, Alsamman Habib, Peter Hamwieh, Aladdin Hassanein, Sameh Saber-Ayad, Maha
source	BioRxiv
abstract	COVID-19, caused by SARS-CoV-2 infection, has already reached pandemic proportions in a matter of a few weeks. At the time of writing this manuscript, the unprecedented public health crisis caused more than 2.5 million cases with a mortality range of 5-7%. The SARS-CoV-2, also called novel Coronavirus, is related to both SARS-CoV and bat SARS. Great efforts have been spent to control the pandemic that has become a significant burden on the health systems in a short time. Since the emergence of the crisis, a great number of researchers started to use the AI tools to identify drugs, diagnosing using CT scan images, scanning body temperature, and classifying the severity of the disease. The emergence of variants of the SARS-CoV-2 genome is a challenging problem with expected serious consequences on the management of the disease. Here, we introduce COVIDier, a deep learning-based software that is enabled to classify the different genomes of Alpha coronavirus, Beta coronavirus, MERS, SARS-CoV-1, SARS-CoV-2, and bronchitis-CoV. COVIDier was trained on 1925 genomes, belonging to the three families of SARS retrieved from NCBI Database to propose a new method to train deep learning model trained on genome data using Multi-layer Perceptron Classifier (MLPClassifier), a deep learning algorithm, that could blindly predict the virus family name from the genome of by predicting the statistically similar genome from training data to the given genome. COVIDier able to predict how close the emerging novel genomes of SARS to the known genomes with accuracy 99%. COVIDier can replace tools like BLAST that consume higher CPU and time.
has issue date	2020-05-04(xsd:dateTime)
bibo:doi	10.1101/2020.05.03.075549
has license	biorxiv
sha1sum (hex)	a121238e9bd618976e23848d9394ec46d07c7cb7
schema:url	https://doi.org/10.1101/2020.05.03.075549
resource representing a document's title	COVIDier: A Deep-learning Tool For Coronaviruses Genome And Virulence Proteins Classification
schema:publication	bioRxiv
resource representing a document's body	covid:a121238e9bd618976e23848d9394ec46d07c7cb7#body_text
is schema:about of	named entity 'reached' named entity 'coronavirus' named entity 'CPU' named entity 'algorithm' named entity 'emerging' »more»

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