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Phylogenetic Analysis of Poliovirus Sequences

Name: Phylogenetic Analysis of Poliovirus Sequences
Creator: Jaume Jorba
Keywords: 0301 basic medicine, 0303 health sciences, Likelihood Functions, 4. Education, Bayes Theorem, Markov Chains, 3. Good health, 03 medical and health sciences, Poliovirus, Humans

descriptionPublicationkeyboard_double_arrow_right Part of book or chapter of book , Article 01 Jan 2016Publisher:Springer New York

Authors: Jaume Jorba;

doi: 10.1007/978-1-4939-3292-4_11

pmid: 26983737

Phylogenetic Analysis of Poliovirus Sequences

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Abstract

Comparative genomic sequencing is a major surveillance tool in the Polio Laboratory Network. Due to the rapid evolution of polioviruses (~1 % per year), pathways of virus transmission can be reconstructed from the pathways of genomic evolution. Here, we describe three main phylogenetic methods; estimation of genetic distances, reconstruction of a maximum-likelihood (ML) tree, and estimation of substitution rates using Bayesian Markov chain Monte Carlo (MCMC). The data set used consists of complete capsid sequences from a survey of poliovirus sequences available in GenBank.

Related Organizations

Centers for Disease Control and Prevention
United States
National Center for Immunization and Respiratory Diseases
United States
Office of Infectious Diseases
United States

Keywords

Likelihood Functions, Bayes Theorem, Markov Chains, Poliovirus, Humans, Capsid Proteins, Monte Carlo Method, Phylogeny, Software, Poliomyelitis

Impact byBIP!

	citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	9
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Top 10%
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Top 10%
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Average