Topological data analysis as a morphometric method: using persistent homology to demarcate a leaf morphospace
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Outros Autores: | , , , , , , , , , , , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | LOCUS Repositório Institucional da UFV |
Texto Completo: | https://doi.org/10.3389/fpls.2018.00553 http://www.locus.ufv.br/handle/123456789/24130 |
Resumo: | Current morphometric methods that comprehensively measure shape cannot compare the disparate leaf shapes found in seed plants and are sensitive to processing artifacts. We explore the use of persistent homology, a topological method applied as a filtration across simplicial complexes (or more simply, a method to measure topological features of spaces across different spatial resolutions), to overcome these limitations. The described method isolates subsets of shape features and measures the spatial relationship of neighboring pixel densities in a shape. We apply the method to the analysis of 182,707 leaves, both published and unpublished, representing 141 plant families collected from 75 sites throughout the world. By measuring leaves from throughout the seed plants using persistent homology, a defined morphospace comparing all leaves is demarcated. Clear differences in shape between major phylogenetic groups are detected and estimates of leaf shape diversity within plant families are made. The approach predicts plant family above chance. The application of a persistent homology method, using topological features, to measure leaf shape allows for a unified morphometric framework to measure plant form, including shapes, textures, patterns, and branching architectures. |
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Otoni, Wagner C.Li, MaoAn, HongAngelovici, RuthieBagaza, ClementBatushansky, AlbertClark, LynnConeva, ViktoriyaDonoghue, Michael J.Edwards, ErikaFajardo, DiegoFang, HuiFrank, Margaret H.Gallaher, TimothyGebken, SarahHill, TheresaJansky, Shelleyet al.2019-03-26T13:58:11Z2019-03-26T13:58:11Z2018-041664462Xhttps://doi.org/10.3389/fpls.2018.00553http://www.locus.ufv.br/handle/123456789/24130Current morphometric methods that comprehensively measure shape cannot compare the disparate leaf shapes found in seed plants and are sensitive to processing artifacts. We explore the use of persistent homology, a topological method applied as a filtration across simplicial complexes (or more simply, a method to measure topological features of spaces across different spatial resolutions), to overcome these limitations. The described method isolates subsets of shape features and measures the spatial relationship of neighboring pixel densities in a shape. We apply the method to the analysis of 182,707 leaves, both published and unpublished, representing 141 plant families collected from 75 sites throughout the world. By measuring leaves from throughout the seed plants using persistent homology, a defined morphospace comparing all leaves is demarcated. Clear differences in shape between major phylogenetic groups are detected and estimates of leaf shape diversity within plant families are made. The approach predicts plant family above chance. The application of a persistent homology method, using topological features, to measure leaf shape allows for a unified morphometric framework to measure plant form, including shapes, textures, patterns, and branching architectures.engFrontiers in Plant ScienceVolume 09, Article 553, Pages 01- 14, April 2018Leaf shapeLeavesMorphologyShapeTopologyTopological data analysisPersistent homologyMorphometricsTopological data analysis as a morphometric method: using persistent homology to demarcate a leaf morphospaceinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfinfo:eu-repo/semantics/openAccessreponame:LOCUS Repositório Institucional da UFVinstname:Universidade Federal de Viçosa (UFV)instacron:UFVORIGINALartigo.pdfartigo.pdftexto completoapplication/pdf5674253https://locus.ufv.br//bitstream/123456789/24130/1/artigo.pdf44982de2c7212a26cf24fa2aa36e19daMD51LICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://locus.ufv.br//bitstream/123456789/24130/2/license.txt8a4605be74aa9ea9d79846c1fba20a33MD52123456789/241302019-03-26 11:01:11.731oai:locus.ufv.br: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Repositório InstitucionalPUBhttps://www.locus.ufv.br/oai/requestfabiojreis@ufv.bropendoar:21452019-03-26T14:01:11LOCUS Repositório Institucional da UFV - Universidade Federal de Viçosa (UFV)false |
dc.title.en.fl_str_mv |
Topological data analysis as a morphometric method: using persistent homology to demarcate a leaf morphospace |
title |
Topological data analysis as a morphometric method: using persistent homology to demarcate a leaf morphospace |
spellingShingle |
Topological data analysis as a morphometric method: using persistent homology to demarcate a leaf morphospace Otoni, Wagner C. Leaf shape Leaves Morphology Shape Topology Topological data analysis Persistent homology Morphometrics |
title_short |
Topological data analysis as a morphometric method: using persistent homology to demarcate a leaf morphospace |
title_full |
Topological data analysis as a morphometric method: using persistent homology to demarcate a leaf morphospace |
title_fullStr |
Topological data analysis as a morphometric method: using persistent homology to demarcate a leaf morphospace |
title_full_unstemmed |
Topological data analysis as a morphometric method: using persistent homology to demarcate a leaf morphospace |
title_sort |
Topological data analysis as a morphometric method: using persistent homology to demarcate a leaf morphospace |
author |
Otoni, Wagner C. |
author_facet |
Otoni, Wagner C. Li, Mao An, Hong Angelovici, Ruthie Bagaza, Clement Batushansky, Albert Clark, Lynn Coneva, Viktoriya Donoghue, Michael J. Edwards, Erika Fajardo, Diego Fang, Hui Frank, Margaret H. Gallaher, Timothy Gebken, Sarah Hill, Theresa Jansky, Shelley et al. |
author_role |
author |
author2 |
Li, Mao An, Hong Angelovici, Ruthie Bagaza, Clement Batushansky, Albert Clark, Lynn Coneva, Viktoriya Donoghue, Michael J. Edwards, Erika Fajardo, Diego Fang, Hui Frank, Margaret H. Gallaher, Timothy Gebken, Sarah Hill, Theresa Jansky, Shelley et al. |
author2_role |
author author author author author author author author author author author author author author author author author |
dc.contributor.author.fl_str_mv |
Otoni, Wagner C. Li, Mao An, Hong Angelovici, Ruthie Bagaza, Clement Batushansky, Albert Clark, Lynn Coneva, Viktoriya Donoghue, Michael J. Edwards, Erika Fajardo, Diego Fang, Hui Frank, Margaret H. Gallaher, Timothy Gebken, Sarah Hill, Theresa Jansky, Shelley et al. |
dc.subject.pt-BR.fl_str_mv |
Leaf shape Leaves Morphology Shape Topology Topological data analysis Persistent homology Morphometrics |
topic |
Leaf shape Leaves Morphology Shape Topology Topological data analysis Persistent homology Morphometrics |
description |
Current morphometric methods that comprehensively measure shape cannot compare the disparate leaf shapes found in seed plants and are sensitive to processing artifacts. We explore the use of persistent homology, a topological method applied as a filtration across simplicial complexes (or more simply, a method to measure topological features of spaces across different spatial resolutions), to overcome these limitations. The described method isolates subsets of shape features and measures the spatial relationship of neighboring pixel densities in a shape. We apply the method to the analysis of 182,707 leaves, both published and unpublished, representing 141 plant families collected from 75 sites throughout the world. By measuring leaves from throughout the seed plants using persistent homology, a defined morphospace comparing all leaves is demarcated. Clear differences in shape between major phylogenetic groups are detected and estimates of leaf shape diversity within plant families are made. The approach predicts plant family above chance. The application of a persistent homology method, using topological features, to measure leaf shape allows for a unified morphometric framework to measure plant form, including shapes, textures, patterns, and branching architectures. |
publishDate |
2018 |
dc.date.issued.fl_str_mv |
2018-04 |
dc.date.accessioned.fl_str_mv |
2019-03-26T13:58:11Z |
dc.date.available.fl_str_mv |
2019-03-26T13:58:11Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://doi.org/10.3389/fpls.2018.00553 http://www.locus.ufv.br/handle/123456789/24130 |
dc.identifier.issn.none.fl_str_mv |
1664462X |
identifier_str_mv |
1664462X |
url |
https://doi.org/10.3389/fpls.2018.00553 http://www.locus.ufv.br/handle/123456789/24130 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.ispartofseries.pt-BR.fl_str_mv |
Volume 09, Article 553, Pages 01- 14, April 2018 |
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openAccess |
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Frontiers in Plant Science |
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Frontiers in Plant Science |
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