About: Tree and rate estimation by local evaluation of heterochronous nucleotide data

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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	Tree and rate estimation by local evaluation of heterochronous nucleotide data
Creator	She, Zhen-Su Zheng, Xiaobin O'brien, John Yang, Zhu Zhu, Huai-Qiu
source	Medline; PMC
abstract	Motivation: Heterochronous gene sequence data is important for characterizing the evolutionary processes of fast-evolving organisms such as RNA viruses. A limited set of algorithms exists for estimating the rate of nucleotide substitution and inferring phylogenetic trees from such data. The authors here present a new method, Tree and Rate Estimation by Local Evaluation (TREBLE) that robustly calculates the rate of nucleotide substitution and phylogeny with several orders of magnitude improvement in computational time. Methods: For the basis of its rate estimation TREBLE novelly utilizes a geometric interpretation of the molecular clock assumption to deduce a local estimate of the rate of nucleotide substitution for triplets of dated sequences. Averaging the triplet estimates via a variance weighting yields a global estimate of the rate. From this value, an iterative refinement procedure relying on statistical properties of the triplets then generates a final estimate of the global rate of nucleotide substitution. The estimated global rate is then utilized to find the tree from the pairwise distance matrix via an UPGMA-like algorithm. Results: Simulation studies show that TREBLE estimates the rate of nucleotide substitution with point estimates comparable with the best of available methods. Confidence intervals are comparable with that of BEAST. TREBLE's phylogenetic reconstruction is significantly improved over the other distance matrix method but not as accurate as the Bayesian algorithm. Compared with three other algorithms, TREBLE reduces computational time by a minimum factor of 3000. Relative to the algorithm with the most accurate estimates for the rate of nucleotide substitution (i.e. BEAST), TREBLE is over 10 000 times more computationally efficient. Availability: Contact: jdobrien@ucla.edu
has issue date	2007-01-15(xsd:dateTime)
bibo:doi	10.1093/bioinformatics/btl577
bibo:pmid	17110369
has license	cc-by-nc
sha1sum (hex)	2e67ee0d485406c4ecd976076ff2112b81d32618
schema:url	https://doi.org/10.1093/bioinformatics/btl577
resource representing a document's title	Tree and rate estimation by local evaluation of heterochronous nucleotide data
has PubMed Central identifier	PMC7187891
has PubMed identifier	17110369
schema:publication	Bioinformatics
resource representing a document's body	covid:2e67ee0d485406c4ecd976076ff2112b81d32618#body_text
is schema:about of	named entity 'comparable' named entity 'processes' named entity 'RNA' named entity 'nucleotide substitution' named entity 'nucleotide substitution' named entity 'Local' named entity 'authors' named entity 'sequences' named entity 'estimate' named entity 'estimates' named entity 'estimation' named entity 'Tree' named entity 'basis' named entity 'triplet' named entity 'Estimation' named entity 'exists' named entity 'algorithm' named entity 'estimates' named entity 'geometric interpretation' named entity 'computational time' named entity 'BEAST' named entity 'statistical' named entity 'data' named entity 'computationally' named entity 'nucleotide substitution' named entity 'algorithm' named entity 'point estimates' named entity 'gene' named entity 'Simulation' named entity 'computational time' named entity 'variance' named entity 'physiology' named entity 'computational time' named entity 'sampling' named entity 'nucleotide substitution' named entity 'bootstrap' named entity 'phylogenetic tree' named entity 'serotype' named entity 'evolutionary model' named entity 'taxa' named entity 'taxa' named entity 'significant difference' named entity 'MRCA' named entity 'topology' named entity 'Kimura' named entity 'non-normality' named entity 'sequence data' named entity 'data set' named entity 'bootstrap' named entity 'Markov process' named entity 'taxa' named entity 'gene sequences' named entity 'variance' named entity 'hemagglutinin' named entity 'algorithm' named entity 'Database' named entity 'heterogeneity' named entity 'evolutionary process' named entity 'variance' named entity 'sampling' named entity 'hidden Markov models' named entity 'UPGMA' named entity 'taxa' named entity 'geometry' named entity 'sequence data' named entity 'expected number' named entity 'multiple genes' named entity 'observed data' named entity 'confidence level' named entity 'nucleotides' named entity 'unit of time' named entity 'sequence data' named entity 'algorithm' named entity 'topology' named entity 'host species' named entity 'sampling' named entity 'algorithm'

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