Abstract
A wide range of metrics between phylogenetic trees are used in evolutionary molecular biology. They are typically based directly on the branching patterns and edge lengths represented by the trees. Metrics have recently been proposed which are based on the information content of distributions of genetic characters induced by the trees. We first show how these metrics lead to a change to the topology of the underlying tree space. Next we show via computational methods that the metrics are stable under changes to the Markov process used to generate characters, at least in the case of 5 taxa. As a result, a Gaussian process defined over the edges of trees can be used to compute the metrics, leading to a substantial computational efficiency over DNA nucleotide-valued Markov process models.
Original language | English |
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Title of host publication | Geometric Science of Information |
Subtitle of host publication | 5th International Conference, GSI 2021, Paris, France, July 21–23, 2021, Proceedings |
Editors | Frank Nielsen, Frédéric Barbaresco |
Place of Publication | Cham, Switzerland |
Publisher | Springer |
Pages | 701-709 |
Number of pages | 9 |
Edition | 1 |
ISBN (Electronic) | 9783030802097 |
ISBN (Print) | 9783030802080 |
DOIs | |
Publication status | Published - 10 Jul 2021 |
Externally published | Yes |
Event | 5th International Conference on Geometric Science of Information, GSI 2021 - Paris, France Duration: 21 Jul 2021 → 23 Jul 2021 Conference number: 5 |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 12829 LNCS |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference
Conference | 5th International Conference on Geometric Science of Information, GSI 2021 |
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Country/Territory | France |
City | Paris |
Period | 21/07/21 → 23/07/21 |