Calculating structural complexity in phylogenies using ancestral ontologies

Autores
Ramirez, Martin Javier; Michalik, Peter
Año de publicación
2014
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Complexity is an important aspect of evolutionary biology, but there are many reasonable concepts of complexity, and its objective measurement is an elusive matter. Here we develop a simple measure of complexity based on counts of elements, incorporating the hierarchical information as represented in anatomical ontologies. Neomorphic and transformational characters are used to identify novelties and individuated morphological regions, respectively. By linking the characters to terms in an anatomical ontology a node-driven approach is implemented, where a node ontology and a complexity score are inferred from the optimization of individual characters on each ancestral or terminal node. From the atomized vector of character scorings, the anatomical ontology is used to integrate the hierarchical structure of morphology in terminals and ancestors. These node ontologies are used to calculate a measure of complexity that can be traced on phylogenetic trees and is harmonious with usual phylogenetic operations. This strategy is compared with a terminal-driven approach, in which the complexity scores are calculated only for terminals, and optimized as a continuous character on the internal nodes. These ideas are applied to a real dataset of 166 araneomorph spider species scored for 393 characters, using Spider Ontology (SPD, https://bioportal.bioontology.org/ontologies/ SPD); complexity scores and transitions are calculated for each node and branch, respectively. This result in a distribution of transitions skewed towards simplification; the transitions in complexity have no apparent correlation with character branch lengths. The node-driven and terminal-driven estimations are generally correlated in the complexity scores, but have higher divergence in the transition values. The structure of the ontology is used to provide complexity scores for organ systems and body parts of the focal groups.
Fil: Ramirez, Martin Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Museo Argentino de Ciencias Naturales "bernardino Rivadavia"; Argentina
Fil: Michalik, Peter. Ernst-Moritz-Arndt-Universität. Zoologisches Institut Und Museum; Alemania
Materia
Anatomical Ontology
Systematics
Automated Reasoning
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/18148
Acceder
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network_name_str CONICET Digital (CONICET)
spelling Calculating structural complexity in phylogenies using ancestral ontologiesRamirez, Martin JavierMichalik, PeterAnatomical OntologySystematicsAutomated Reasoninghttps://purl.org/becyt/ford/1.6https://purl.org/becyt/ford/1Complexity is an important aspect of evolutionary biology, but there are many reasonable concepts of complexity, and its objective measurement is an elusive matter. Here we develop a simple measure of complexity based on counts of elements, incorporating the hierarchical information as represented in anatomical ontologies. Neomorphic and transformational characters are used to identify novelties and individuated morphological regions, respectively. By linking the characters to terms in an anatomical ontology a node-driven approach is implemented, where a node ontology and a complexity score are inferred from the optimization of individual characters on each ancestral or terminal node. From the atomized vector of character scorings, the anatomical ontology is used to integrate the hierarchical structure of morphology in terminals and ancestors. These node ontologies are used to calculate a measure of complexity that can be traced on phylogenetic trees and is harmonious with usual phylogenetic operations. This strategy is compared with a terminal-driven approach, in which the complexity scores are calculated only for terminals, and optimized as a continuous character on the internal nodes. These ideas are applied to a real dataset of 166 araneomorph spider species scored for 393 characters, using Spider Ontology (SPD, https://bioportal.bioontology.org/ontologies/ SPD); complexity scores and transitions are calculated for each node and branch, respectively. This result in a distribution of transitions skewed towards simplification; the transitions in complexity have no apparent correlation with character branch lengths. The node-driven and terminal-driven estimations are generally correlated in the complexity scores, but have higher divergence in the transition values. The structure of the ontology is used to provide complexity scores for organ systems and body parts of the focal groups.Fil: Ramirez, Martin Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Museo Argentino de Ciencias Naturales "bernardino Rivadavia"; ArgentinaFil: Michalik, Peter. Ernst-Moritz-Arndt-Universität. Zoologisches Institut Und Museum; AlemaniaWiley Blackwell Publishing, Inc2014-04-22info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/18148Ramirez, Martin Javier; Michalik, Peter; Calculating structural complexity in phylogenies using ancestral ontologies; Wiley Blackwell Publishing, Inc; Cladistics; 30; 6; 22-4-2014; 635-6490748-3007CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1111/cla.12075info:eu-repo/semantics/altIdentifier/url/http://onlinelibrary.wiley.com/doi/10.1111/cla.12075/abstractinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2026-08-25T15:07:51Zoai:ri.conicet.gov.ar:11336/18148instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982026-08-25 15:07:52.065CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Calculating structural complexity in phylogenies using ancestral ontologies
title Calculating structural complexity in phylogenies using ancestral ontologies
spellingShingle Calculating structural complexity in phylogenies using ancestral ontologies
Ramirez, Martin Javier
Anatomical Ontology
Systematics
Automated Reasoning
title_short Calculating structural complexity in phylogenies using ancestral ontologies
title_full Calculating structural complexity in phylogenies using ancestral ontologies
title_fullStr Calculating structural complexity in phylogenies using ancestral ontologies
title_full_unstemmed Calculating structural complexity in phylogenies using ancestral ontologies
title_sort Calculating structural complexity in phylogenies using ancestral ontologies
dc.creator.none.fl_str_mv Ramirez, Martin Javier
Michalik, Peter
author Ramirez, Martin Javier
author_facet Ramirez, Martin Javier
Michalik, Peter
author_role author
author2 Michalik, Peter
author2_role author
dc.subject.none.fl_str_mv Anatomical Ontology
Systematics
Automated Reasoning
topic Anatomical Ontology
Systematics
Automated Reasoning
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.6
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Complexity is an important aspect of evolutionary biology, but there are many reasonable concepts of complexity, and its objective measurement is an elusive matter. Here we develop a simple measure of complexity based on counts of elements, incorporating the hierarchical information as represented in anatomical ontologies. Neomorphic and transformational characters are used to identify novelties and individuated morphological regions, respectively. By linking the characters to terms in an anatomical ontology a node-driven approach is implemented, where a node ontology and a complexity score are inferred from the optimization of individual characters on each ancestral or terminal node. From the atomized vector of character scorings, the anatomical ontology is used to integrate the hierarchical structure of morphology in terminals and ancestors. These node ontologies are used to calculate a measure of complexity that can be traced on phylogenetic trees and is harmonious with usual phylogenetic operations. This strategy is compared with a terminal-driven approach, in which the complexity scores are calculated only for terminals, and optimized as a continuous character on the internal nodes. These ideas are applied to a real dataset of 166 araneomorph spider species scored for 393 characters, using Spider Ontology (SPD, https://bioportal.bioontology.org/ontologies/ SPD); complexity scores and transitions are calculated for each node and branch, respectively. This result in a distribution of transitions skewed towards simplification; the transitions in complexity have no apparent correlation with character branch lengths. The node-driven and terminal-driven estimations are generally correlated in the complexity scores, but have higher divergence in the transition values. The structure of the ontology is used to provide complexity scores for organ systems and body parts of the focal groups.
Fil: Ramirez, Martin Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Museo Argentino de Ciencias Naturales "bernardino Rivadavia"; Argentina
Fil: Michalik, Peter. Ernst-Moritz-Arndt-Universität. Zoologisches Institut Und Museum; Alemania
description Complexity is an important aspect of evolutionary biology, but there are many reasonable concepts of complexity, and its objective measurement is an elusive matter. Here we develop a simple measure of complexity based on counts of elements, incorporating the hierarchical information as represented in anatomical ontologies. Neomorphic and transformational characters are used to identify novelties and individuated morphological regions, respectively. By linking the characters to terms in an anatomical ontology a node-driven approach is implemented, where a node ontology and a complexity score are inferred from the optimization of individual characters on each ancestral or terminal node. From the atomized vector of character scorings, the anatomical ontology is used to integrate the hierarchical structure of morphology in terminals and ancestors. These node ontologies are used to calculate a measure of complexity that can be traced on phylogenetic trees and is harmonious with usual phylogenetic operations. This strategy is compared with a terminal-driven approach, in which the complexity scores are calculated only for terminals, and optimized as a continuous character on the internal nodes. These ideas are applied to a real dataset of 166 araneomorph spider species scored for 393 characters, using Spider Ontology (SPD, https://bioportal.bioontology.org/ontologies/ SPD); complexity scores and transitions are calculated for each node and branch, respectively. This result in a distribution of transitions skewed towards simplification; the transitions in complexity have no apparent correlation with character branch lengths. The node-driven and terminal-driven estimations are generally correlated in the complexity scores, but have higher divergence in the transition values. The structure of the ontology is used to provide complexity scores for organ systems and body parts of the focal groups.
publishDate 2014
dc.date.none.fl_str_mv 2014-04-22
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/18148
Ramirez, Martin Javier; Michalik, Peter; Calculating structural complexity in phylogenies using ancestral ontologies; Wiley Blackwell Publishing, Inc; Cladistics; 30; 6; 22-4-2014; 635-649
0748-3007
CONICET Digital
CONICET
url http://hdl.handle.net/11336/18148
identifier_str_mv Ramirez, Martin Javier; Michalik, Peter; Calculating structural complexity in phylogenies using ancestral ontologies; Wiley Blackwell Publishing, Inc; Cladistics; 30; 6; 22-4-2014; 635-649
0748-3007
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1111/cla.12075
info:eu-repo/semantics/altIdentifier/url/http://onlinelibrary.wiley.com/doi/10.1111/cla.12075/abstract
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Wiley Blackwell Publishing, Inc
publisher.none.fl_str_mv Wiley Blackwell Publishing, Inc
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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