3Computational Predictors of the Predominant Protein Function: SARS-CoV-2 Case
Carlos Polanco1,2*, Manlio F. Márquez3 and Gilberto Vargas-Alarcón4
1Department of Electromechanical Instrumentation, Instituto Nacional de Cardiología “Ignacio Chávez”, México City, México
2Department of Mathematics, Faculty of Sciences, Universidad Nacional Autónoma de México, México City, México
3Clinical Research Center, Instituto Nacional de Cardiología “Ignacio Chávez”, México City, México
4Research Center, Instituto Nacional de Cardiología “Ignacio Chávez”, México City, México
Abstract
In this chapter, we describe the main molecular features of SARS-CoV-2 that cause COVID-19 disease, as well as a high-efficiency computational prediction called Polarity Index Method®. We also introduce a molecular classification of the RNA virus and DNA virus families and two main classifications: supervised and non-supervised algorithms of the predictions of the predominant function of proteins. Finally, some results obtained by the proposed non-supervised method are given, as well as some particularities found about the linear representation of proteins.
Keywords: Adenoviridae, advantages, algorithms, Anelloviridae, Arenaviridae, Caliciviridae, computational predictions, Coronaviridae family, disadvantages, DNA virus, Herpesviridae, Herpesviridae, linear representation, non-supervised algorithms, Papillomaviridae, Parvoviridae, Picornaviridae, PIM® profile, Polarity Index Method®, Poxviridae, putative proteins, ...
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