H
Hirohisa Kishino
Researcher at University of Tokyo
Publications - 189
Citations - 21590
Hirohisa Kishino is an academic researcher from University of Tokyo. The author has contributed to research in topics: Population & Phylogenetic tree. The author has an hindex of 47, co-authored 184 publications receiving 20466 citations. Previous affiliations of Hirohisa Kishino include Tokyo University of Agriculture and Technology & Graduate University for Advanced Studies.
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Dating of the human-ape splitting by a molecular clock of mitochondrial DNA.
TL;DR: A new statistical method for estimating divergence dates of species from DNA sequence data by a molecular clock approach is developed, and this dating may pose a problem for the widely believed hypothesis that the bipedal creatureAustralopithecus afarensis, which lived some 3.7 million years ago, was ancestral to man and evolved after the human-ape splitting.
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Evaluation of the maximum likelihood estimate of the evolutionary tree topologies from DNA sequence data, and the branching order in hominoidea
Hirohisa Kishino,Masami Hasegawa +1 more
TL;DR: A new method for estimating the variance of the difference between log likelihood of different tree topologies is developed by expressing it explicitly in order to evaluate the maximum likelihood branching order among Hominoidea.
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Estimating the rate of evolution of the rate of molecular evolution.
TL;DR: A simple model for the evolution of the rate of molecular evolution with a Bayesian approach can serve as the basis for estimating dates of important evolutionary events even in the absence of the assumption of constant rates among evolutionary lineages.
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Divergence time and evolutionary rate estimation with multilocus data.
TL;DR: Bayesian methods for estimating evolutionary divergence times are extended to multigene data sets, and a technique is described for detecting correlated changes in evolutionary rates among genes.
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Maximum likelihood inference of protein phylogeny and the origin of chloroplasts
TL;DR: A maximum likelihood method based on a Markov model that takes into account the unequal transition probabilities among pairs of amino acids and does not assume constancy of rate among different lineages is expected to be powerful in inferring phylogeny among distantly related proteins.