English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Inference of the marginal likelihood of sample allele configurations usingbackward algorithms yields identical results with the Kingman coalescent, theMoran model, and the diffusion model (up to a scaling of time). For inferenceof probabilities of ancestral population allele frequencies at any given pointin the past - either of discrete ancestral allele configurations as in thecoalescent, or of ancestral allele proportions as in the backward diffusion -backward approaches need to be combined with corresponding forward ones. Thisis done in so-called forward-backward algorithms. In this article, we utilizeorthogonal polynomials in forward-backward algorithms. They enable efficientcalculation of past allele configurations of an extant sample and probabilitiesof ancestral population allele frequencies in equilibrium and innon-equilibrium. We show that the genealogy of a sample is fully described bythe backward polynomial expansion of the marginal likelihood of its alleleconfiguration.

Forward-backward algorithms with a biallelic mutation-drift model: Orthogonal polynomials, and a coalescent/urn-model based approach