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Two metrics on rooted unordered trees with labels

BACKGROUND: The early development of a zygote can be mathematically described by a developmental tree. To compare developmental trees of different species, we need to define distances on trees. If children cells after a division are not distinguishable, developmental trees are represented by the spa...

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Autor principal: Wang, Yue
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9169382/
https://www.ncbi.nlm.nih.gov/pubmed/35668521
http://dx.doi.org/10.1186/s13015-022-00220-0
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author Wang, Yue
author_facet Wang, Yue
author_sort Wang, Yue
collection PubMed
description BACKGROUND: The early development of a zygote can be mathematically described by a developmental tree. To compare developmental trees of different species, we need to define distances on trees. If children cells after a division are not distinguishable, developmental trees are represented by the space [Formula: see text] of rooted trees with possibly repeated labels, where all vertices are unordered. If children cells after a division are partially distinguishable, developmental trees are represented by the space [Formula: see text] of rooted trees with possibly repeated labels, where vertices can be ordered or unordered. RESULTS: On [Formula: see text] , the space of rooted unordered trees with possibly repeated labels, we define two metrics: the best-match metric and the left-regular metric, which show some advantages over existing methods. On [Formula: see text] , the space of rooted labeled trees with ordered or unordered vertices, there is no metric, and we define a semimetric, which is a variant of the best-match metric. To compute the best-match distance between two trees, the expected time complexity and worst-case time complexity are both [Formula: see text] , where n is the tree size. To compute the left-regular distance between two trees, the expected time complexity is [Formula: see text] , and the worst-case time complexity is [Formula: see text] . CONCLUSIONS: For rooted labeled trees with (fully/partially) unordered vertices, we define metrics (semimetric) that have fast algorithms to compute and have advantages over existing methods. Such trees also appear outside of developmental biology, and such metrics can be applied to other types of trees which have more extensive applications, especially in molecular biology.
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spelling pubmed-91693822022-06-07 Two metrics on rooted unordered trees with labels Wang, Yue Algorithms Mol Biol Research BACKGROUND: The early development of a zygote can be mathematically described by a developmental tree. To compare developmental trees of different species, we need to define distances on trees. If children cells after a division are not distinguishable, developmental trees are represented by the space [Formula: see text] of rooted trees with possibly repeated labels, where all vertices are unordered. If children cells after a division are partially distinguishable, developmental trees are represented by the space [Formula: see text] of rooted trees with possibly repeated labels, where vertices can be ordered or unordered. RESULTS: On [Formula: see text] , the space of rooted unordered trees with possibly repeated labels, we define two metrics: the best-match metric and the left-regular metric, which show some advantages over existing methods. On [Formula: see text] , the space of rooted labeled trees with ordered or unordered vertices, there is no metric, and we define a semimetric, which is a variant of the best-match metric. To compute the best-match distance between two trees, the expected time complexity and worst-case time complexity are both [Formula: see text] , where n is the tree size. To compute the left-regular distance between two trees, the expected time complexity is [Formula: see text] , and the worst-case time complexity is [Formula: see text] . CONCLUSIONS: For rooted labeled trees with (fully/partially) unordered vertices, we define metrics (semimetric) that have fast algorithms to compute and have advantages over existing methods. Such trees also appear outside of developmental biology, and such metrics can be applied to other types of trees which have more extensive applications, especially in molecular biology. BioMed Central 2022-06-06 /pmc/articles/PMC9169382/ /pubmed/35668521 http://dx.doi.org/10.1186/s13015-022-00220-0 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Wang, Yue
Two metrics on rooted unordered trees with labels
title Two metrics on rooted unordered trees with labels
title_full Two metrics on rooted unordered trees with labels
title_fullStr Two metrics on rooted unordered trees with labels
title_full_unstemmed Two metrics on rooted unordered trees with labels
title_short Two metrics on rooted unordered trees with labels
title_sort two metrics on rooted unordered trees with labels
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9169382/
https://www.ncbi.nlm.nih.gov/pubmed/35668521
http://dx.doi.org/10.1186/s13015-022-00220-0
work_keys_str_mv AT wangyue twometricsonrootedunorderedtreeswithlabels