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Algorithms for Molecular Biology
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A polynomial time algorithm for calculating the probability of a ranked gene tree given a species tree

Authors: Stadler Tanja; Degnan James H.;
APC: 1,023.84 EUR

A polynomial time algorithm for calculating the probability of a ranked gene tree given a species tree

Abstract

Background The ancestries of genes form gene trees which do not necessarily have the same topology as the species tree due to incomplete lineage sorting. Available algorithms determining the probability of a gene tree given a species tree require exponential computational runtime. Results In this paper, we provide a polynomial time algorithm to calculate the probability of a ranked gene tree topology for a given species tree, where a ranked tree topology is a tree topology with the internal vertices being ordered. The probability of a gene tree topology can thus be calculated in polynomial time if the number of orderings of the internal vertices is a polynomial number. However, the complexity of calculating the probability of a gene tree topology with an exponential number of rankings for a given species tree remains unknown. Conclusions Polynomial algorithms for calculating ranked gene tree probabilities may become useful in developing methodology to infer species trees based on a collection of gene trees, leading to a more accurate reconstruction of ancestral species relationships.

Algorithms for Molecular Biology, 7

ISSN:1748-7188

Keywords

Applied Mathematics, Research, Anomalous gene trees, Populations and Evolution (q-bio.PE), Coalescent history, Dynamic programming, Incomplete lineage sorting, Computational Theory and Mathematics, Structural Biology, FOS: Biological sciences, Quantitative Biology - Populations and Evolution, Molecular Biology

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
11
Average
Average
Average
Green
gold