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Data from: Mixed linear model approach for mapping quantitative trait loci underlying crop seed traits
负责人:
关键词:
software qtl mapping seed traits mixed linear model gene-environment interaction
DOI:
doi:10.5061/dryad.8311n
摘要:
by Markov chain Monte Carlo algorithm for Gaussian mixed linear model via Gibbs sampling. Monte Carlo simulations were performed to investigate the reliability and efficiency
Data from: Integrating continuous stocks and flows into state-and-transition simulation models of landscape change
负责人:
关键词:
Markov chain;ST-Sim software;Modeling;systems dynamics;carbon budget;stochastic;land use change;spatial;landscape dynamics;Holocene;landscape ecology
DOI:
doi:10.5061/dryad.6939c
摘要:
with a STSM of LULC change for the state of Hawai'i, USA. In this example, continuous stocks are pools of terrestrial C, while the flows are the possible fluxes
Data from: Drivers of diversification in individual life courses
负责人:
关键词:
Population: dynamics;Ecology: populations;Population: structure;Density Dependence;Macaca mulatta
DOI:
doi:10.5061/dryad.p2c6r
摘要:
ng an individual's life in a stage-structured population. We quantify heterogeneity by measuring population entropy of a Markov chain, which computes the rate
Fully Bayesian Analysis of RNA-seq Counts for the Detection of Gene Expression Heterosis
负责人:
关键词:
Genetics Molecular Biology Biotechnology 69999 Biological Sciences not elsewhere classified 19999 Mathematical Sciences not elsewhere classified 110309 Infectious Diseases Plant Biology
DOI:
doi:10.6084/m9.figshare.6949499
摘要:
parallelized Markov chain Monte Carlo algorithm ameliorates the computational burden. We use our method to detect gene expression heterosis in a two-hybrid plant
Data from: Dispersal largely explains the Gondwanan distribution of the ancient tropical clusioid plant clade
负责人:
关键词:
Bonnetiaceae;Podostemaceae;vicariance.;Hypericaceae;Dispersal;Clusiaceae;Cretaceous;Cenozic;Calophyllaceae;Malpighiales;Gondwana
DOI:
doi:10.5061/dryad.q4h2r
摘要:
and divergence times of the clusioid clade using a Bayesian Markov chain Monte Carlo approach. Ancestral Area Reconstructions (AARs) were then conducted
Data from: A Bayesian approach for detecting the impact of mass-extinction events on molecular phylogenies when rates of lineage diversification ma
负责人:
关键词:
Compound Poisson Process Model;Birth-Death Stochastic-Branching Process;Bayesian inference;Lineage Diversification Rates;phylogeny;28 Mass Extinction;speciation
DOI:
doi:10.5061/dryad.v16ns
摘要:
ameters of the model are then estimated in a Bayesian statistical framework using a reversible-jump Markov chain Monte Carlo algorithm. This Bayesian approach enables
Data from: Estimating range expansion of wildlife in heterogeneous landscapes: a spatially explicit state-space matrix model coupled with an improved
负责人:
Osada, Yutaka
关键词:
population dynamic
DOI:
doi:10.5061/dryad.pt38f8s
摘要:
numerical integration technique (Markov chain Monte Carlo with particle filters). In particular, we explored the environmental drivers of inhomogeneous range expansion
Fully Bayesian analysis of RNA-seq counts for the detection of gene expression heterosis
负责人:
关键词:
Genetics Molecular Biology Biotechnology 69999 Biological Sciences not elsewhere classified 19999 Mathematical Sciences not elsewhere classified 110309 Infectious Diseases Plant Biology
DOI:
doi:10.6084/m9.figshare.6949499.v1
摘要:
an efficient parallelized Markov chain Monte Carlo algorithm ameliorates the computational burden. We use our method to detect gene expression heterosis
Data from: The relationship between dN/dS and scaled selection coefficients
负责人:
关键词:
dN\/dS;mutation-selection models;Markov models of sequence evolution;scaled selection coefficients
DOI:
doi:10.5061/dryad.51sq0
摘要:
w benchmarking strategy of dN/dS inferences against MutSel simulations and demonstrate that the widely-used Goldman-Yang-style dN/dS models yield subst
Data from: Disentangling the effects of geographic and ecological isolation on genetic differentiation
负责人:
关键词:
Isolation by ecology;spatial genetics;isolation by distance;Zea mays;Landscape Genetics;Homo Sapiens;isolation by environment;partial Mantel test
DOI:
doi:10.5061/dryad.24kp5
摘要:
are estimated using a Markov chain Monte Carlo algorithm. We call this method Bayesian Estimation of Differentiation in Alleles by Spatial Structure

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