Evidence map›Paper›PMID 29893954›Full record

ArticleMolecular biology and evolution2018

Theoretical Foundation of the RelTime Method for Estimating Divergence Times from Variable Evolutionary Rates.

Koichiro Tamura, Qiqing Tao, Sudhir Kumar

Abstract readEvaluation Study
In one paragraph

Article in Molecular biology and evolution, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 134 papers.

0numbers the graph read from it
0cells of the map it votes in
134citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

134 citing papers in PubMed.

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  6. Genomic and physiological characterization of Aliivibrio sp. REG001485: A specialized functional ecotype for long-term bioluminescent signaling.Brazilian journal of microbiology : [publication of the Brazilian Society for Microbiology] · 2026
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  12. Characterization ofMicrobiology spectrum · 2026
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74 more citing papers are in PubMed but not listed here.

4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Koichiro TamuraDepartment of Biological Sciences, Tokyo Metropolitan University, Hachioji, Tokyo, Japan.
Qiqing TaoInstitute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, PA.
Sudhir KumarInstitute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, PA.

Funding

Inferring molecular evolutionary rates and divergence datesR01GM126567 · NIGMS · TEMPLE UNIV OF THE COMMONWEALTH · PI KUMAR, SUDHIR · 2018 to 2020
$951k
NIGMS NIH HHS R01 GM126567
6 · The paper itself

Abstract

RelTime estimates divergence times by relaxing the assumption of a strict molecular clock in a phylogeny. It shows excellent performance in estimating divergence times for both simulated and empirical molecular sequence data sets in which evolutionary rates varied extensively throughout the tree. RelTime is computationally efficient and scales well with increasing size of data sets. Until now, however, RelTime has not had a formal mathematical foundation. Here, we show that the basis of the RelTime approach is a relative rate framework (RRF) that combines comparisons of evolutionary rates in sister lineages with the principle of minimum rate change between evolutionary lineages and their respective descendants. We present analytical solutions for estimating relative lineage rates and divergence times under RRF. We also discuss the relationship of RRF with other approaches, including the Bayesian framework. We conclude that RelTime will be useful for phylogenies with branch lengths derived not only from molecular data, but also morphological and biochemical traits.

Indexed as

Biological EvolutionGenetic Techniques

Identifiers

PMID29893954
PMCPMC5995221

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.