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Biologically feasible gene trees, reconciliation maps and informative triples

Overview of attention for article published in Algorithms for Molecular Biology, August 2017
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Title
Biologically feasible gene trees, reconciliation maps and informative triples
Published in
Algorithms for Molecular Biology, August 2017
DOI 10.1186/s13015-017-0114-z
Pubmed ID
Authors

Marc Hellmuth

Abstract

The history of gene families-which are equivalent to event-labeled gene trees-can be reconstructed from empirically estimated evolutionary event-relations containing pairs of orthologous, paralogous or xenologous genes. The question then arises as whether inferred event-labeled gene trees are biologically feasible, that is, if there is a possible true history that would explain a given gene tree. In practice, this problem is boiled down to finding a reconciliation map-also known as DTL-scenario-between the event-labeled gene trees and a (possibly unknown) species tree. In this contribution, we first characterize whether there is a valid reconciliation map for binary event-labeled gene trees T that contain speciation, duplication and horizontal gene transfer events and some unknown species tree S in terms of "informative" triples that are displayed in T and provide information of the topology of S. These informative triples are used to infer the unknown species tree S for T. We obtain a similar result for non-binary gene trees. To this end, however, the reconciliation map needs to be further restricted. We provide a polynomial-time algorithm to decide whether there is a species tree for a given event-labeled gene tree, and in the positive case, to construct the species tree and the respective (restricted) reconciliation map. However, informative triples as well as DTL-scenarios have their limitations when they are used to explain the biological feasibility of gene trees. While reconciliation maps imply biological feasibility, we show that the converse is not true in general. Moreover, we show that informative triples neither provide enough information to characterize "relaxed" DTL-scenarios nor non-restricted reconciliation maps for non-binary biologically feasible gene trees.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 1 8%
Unknown 12 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 23%
Researcher 3 23%
Student > Bachelor 2 15%
Student > Master 2 15%
Student > Doctoral Student 1 8%
Other 0 0%
Unknown 2 15%
Readers by discipline Count As %
Agricultural and Biological Sciences 4 31%
Computer Science 2 15%
Biochemistry, Genetics and Molecular Biology 1 8%
Mathematics 1 8%
Medicine and Dentistry 1 8%
Other 2 15%
Unknown 2 15%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 03 September 2018.
All research outputs
#18,569,430
of 22,999,744 outputs
Outputs from Algorithms for Molecular Biology
#197
of 264 outputs
Outputs of similar age
#242,237
of 315,948 outputs
Outputs of similar age from Algorithms for Molecular Biology
#3
of 7 outputs
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