Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

A two-stage pruning algorithm for likelihood computation for a population tree.

Genetics - 1 Oct 2008

RoyChoudhury Arindam, Felsenstein Joseph, Thompson Elizabeth A

Abstract excerpt

We have developed a pruning algorithm for likelihood estimation of a tree of populations. This algorithm enables us to compute the likelihood for large trees. Thus, it gives an efficient way of obtaining the maximum-likelihood estimate (MLE) for a given tree topology. Our method utilizes the diff...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Algorithms
Share to Evolution, Molecular
Share to Genetics, Population

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Likelihood Functions

Share to Polymorphism, Single Nucleotide

Source

Open in PubMed Open full text

Identifiers

PMID: 18780754
DOI: 10.1534/genetics.107.085753
PMCID: PMC2567359

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 2 Sept 2026. Prepared record publication-18780754-2026-09-02.2. Manifest publication-graph-cohort-2026-09-02.2.

Source receipt: PubMed via Helena Literature Corpus, retrieved 2 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

A two-stage pruning algorithm for likelihood computation for a population tree.PMID 18780754Read ↗

Ascertainment correction for a population tree via a pruning algorithm for likelihood computation.Semantic proximity Read ↗

A fast likelihood approach for estimation of large phylogenies from continuous trait data.Semantic proximity Read ↗

A coalescent-based method for population tree inference with haplotypes.Semantic proximity Read ↗

Exact computation of coalescent likelihood for panmictic and subdivided populations under the infinite sites model.Semantic proximity Read ↗

An approximate likelihood for genetic data under a model with recombination and population splitting.Semantic proximity Read ↗

Usefulness of single nucleotide polymorphism data for estimating population parameters.Semantic proximity Read ↗

LAMARC 2.0: maximum likelihood and Bayesian estimation of population parameters.Semantic proximity Read ↗

A simple method for computing exact probabilities of mutation numbers.Semantic proximity Read ↗

Maximum-likelihood estimation of relatedness.Semantic proximity Read ↗

Joint likelihood-free inference of the number of selected single nucleotide polymorphisms and their selection coefficients in an evolving population.Semantic proximity Read ↗

Population genomics based on low coverage sequencing: how low should we go?Semantic proximity Read ↗

Maximum likelihood and Bayesian methods for estimating the distribution of selective effects among classes of mutations using DNA polymorphism data.Semantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.