activity
20112020
most citedStochastic Modeling and Simulation of Viral Evolution

11 citations · 22 across the 3 of their papers we have counts for

collaborators

5 papers

q-bio.PE2020★ 3 cited

Temporal data series of COVID-19 epidemics in the USA, Asia and Europe suggests a selective sweep of SARS-CoV-2 Spike D614G variant

Taima N. Furuyama, Fernando Antoneli, Isabel M. V. G. Carvalho +2

The COVID-19 pandemic started in Wuhan, China, and caused the worldwide spread of the RNA virus SARS-CoV-2, the causative agent of COVID-19. Because of its mutational rate, wide ge…

q-bio.PE2017★ 11 cited

Stochastic Modeling and Simulation of Viral Evolution

Luiza Guimarães, Diogo Castro, Bruno Gorzoni +2

RNA viruses comprise vast populations of closely related, but highly genetically diverse, entities known as quasispecies. Understanding the mechanisms by which this extreme diversi…

q-bio.QM2014★ 8 cited

Estimation of genetic diversity in viral populations from next generation sequencing data with extremely deep coverage

Jean P. Zukurov, Sieberth do Nascimento-Brito, Angela C. Volpini +3

In this paper we propose a method and discuss its computational implementation as an integrated tool for the analysis of viral genetic diversity on data generated by high-throughpu…

q-bio.PE2012

Virus Replication as a Phenotypic Version of Polynucleotide Evolution

Fernando Antoneli, Francisco Bosco, Diogo Castro +1

In this paper we revisit and adapt to viral evolution an approach based on the theory of branching process advanced by Demetrius, Schuster and Sigmund ("Polynucleotide evolution an…

q-bio.PE2011

Viral Evolution and Adaptation as a Multivariate Branching Process

Fernando Antoneli, Francisco Bosco, Diogo Castro +1

In the present work we analyze the problem of adaptation and evolution of RNA virus populations, by defining the basic stochastic model as a multivariate branching process in close…