Stochastic mapping of morphological characters.

By John P. Huelsenbeck, Rasmus Nielsen, Jonathan P. Bollback. Systematic Biology, 2003

883 citations recorded by the source corpus.

Subfields: Genetics, Molecular Biology, Paleontology

View Paper: https://www.semanticscholar.org/paper/f1e0d37091af6e91855bb3887488d0f064231531

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Citations in the corpus

Phylogeny and the Evolution of Floral Diversity in Pedicularis (Orobanchaceae) (2005, methodology): “…also provides estimates of the uncertainty (variance) associated with inferences of character evolution on a given phylogeny (Nielsen 2002) and, if applied to a set of candidate trees, can be used to make inferences while allowing for uncertainty in the phylogeny itself (Huelsenbeck et al. 2003).”
Two new graphical methods for mapping trait evolution on phylogenies (2013, background): “1) in proportion to their probability conditioned on a model (Neilsen 2002; Huelsenbeck, Nielsen & Bollback 2003).”
Evolutionary Perspectives on Seed Consumption and Dispersal by Fishes (2007, methodology): “We reconstructed the diet of ancestral nodes by applying stochastic likelihood methods for categorical data (Huelsenbeck et al. 2003), using the software package Mesquite (Maddison and Maddison 2006).”
phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things) (2023, methodology): “1 Stochastic character mapping 119 Perhaps the most important and widely-used discrete character method of phytools is a technique referred 120 to as “stochastic character mapping” (Huelsenbeck et al. 2003).”
Flammable biomes dominated by eucalypts originated at the Cretaceous-Palaeogene boundary. (2011, methodology): “The advantage of the Bayesian approach over parsimony and ML mapping is that uncertainty in parameters can be accommodated by using MCMC samples from their respective posterior distribution”
General quantitative genetic methods for comparative biology: phylogenies, taxonomies and multi‐trait models for continuous and categorical characters (2010, methodology): “…the relevant parameters also, using MCMC. Alternative methods exist, mainly based around models of substitutions in DNA sequences (Pagel, 1994; Huelsenbeck et al., 2003; Pagel & Meade, 2006), but Felsenstein (2005) gives a persuasive argument as to why the quantitative genetic approach is to…”
Extended phylogeny of Aquilegia: the biogeographical and ecological patterns of two simultaneous but contrasting radiations (2010, methodology): “We applied the Bayesian mutational mapping approach (BMM) (Nielsen 2002; Huelsenbeck et al. 2003) for mapping the characters, using the post-burn-in tree file”
Directional asymmetry of long‐distance dispersal and colonization could mislead reconstructions of biogeography (2005, neutral): “…inference has the advantage over both parsimony and ML methods of trait reconstruction of taking phylogenetic uncertainty, such as topology, parameter values, and branch length estimations, into account (Huelsenbeck & Bollback, 2001; Huelsenbeck et al., 2003; Pagel et al., 2004; Ronquist, 2004).”
Bayesian estimation of the global biogeographical history of the Solanaceae (2017, methodology): “Stochastic mapping (Nielsen, 2002; Huelsenbeck et al., 2003) is a simulation approach that builds on likelihood models of trait evolution and, in addition to estimating ancestral states at nodes, provides possible histories of changes along branches.”
Modern Phylogenetic Comparative Methods and Their Application in Evolutionary Biology (2014, methodology): “The first plotting method for comparative data that I am going to describe is the relatively simple approach of visualizing the reconstructed history of a discretely valued character trait obtained from a phylogenetic method called stochastic character mapping (Nielsen 2002; Huelsenbeck et al. 2003)”
An Evolutionary-Network Model Reveals Stratified Interactions in the V3 Loop of the HIV-1 Envelope (2007, methodology): “Phylogenetic methods based on ancestral reconstruction have been demonstrated to be robust to heterotachy [37] and variation in substitution rates across sites as well [51].”
SIMMAP: Stochastic character mapping of discrete traits on phylogenies (2006, methodology): “In addition to implementing the above approach of stochastic posterior character mapping, SIMMAP also allows sampling from posterior predictive densities to evaluate the significance of hypotheses [16,23].”