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This program optimizes distributions for each node of a phylogeny by favouring vicariance events and minimizing the number of assumed dispersals and extinctions.
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Both methods have the advantage of enabling direct calibration on one or more nodes of a phylogeny.
We introduce the use of explicit phylogenetic methods to reconstruct the ancestral presence or absence of proteins at the interior nodes of a phylogeny of eukaryote species.
Comparative phylogenetic methods do so in a formal framework using stochastic models of the evolutionary process that implicitly or explicitly assume some probabilistic distribution of ancestral states over internal nodes of a phylogeny [ 1- 3, 47, 69].
To describe the evolution of a protein, being able to study ancestral sequences at different nodes of a phylogeny would obviously provide historically relevant information that is not available otherwise [ 70].
It treats phenotypic measurements at the terminal nodes of a phylogeny as sample observations and relies on a linear regression with L2-Norm regularization, allowing phenotypic rates to vary at each branch.
The Brownian motion (BM) model (Felsenstein, 1985) assumes that the trait of a leaf node in a phylogeny develops as a random walk starting from the ancestral root.
Local plant-soil associations are commonly studied at the species-level, while associations at the level of nodes within a phylogeny have been less well explored.
In this approach, a matrix of ethnomedicinal use was composed and used to identify nodes in a phylogeny of Pterocarpus (Fabaceae), which have more medicinal taxa related to a specific category of use than expected by chance.
Ellingson et al. [ 56] showed that this approach improved both topologies and node support for a phylogeny of fish.
It could also be applied to a chosen node of the phylogeny, for instance to address specific questions of trait evolution.
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