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Towards a bioinformatics of patterning: a computational approach to understanding regulative morphogenesis

The mechanisms underlying the regenerative abilities of certain model species are of central importance to the basic understanding of pattern formation. Complex organisms such as planaria and salamanders exhibit an exceptional capacity to regenerate complete body regions and organs from amputated pi...

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Detalles Bibliográficos
Autores principales: Lobo, Daniel, Malone, Taylor J., Levin, Michael
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Company of Biologists 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3575650/
https://www.ncbi.nlm.nih.gov/pubmed/23429669
http://dx.doi.org/10.1242/bio.20123400
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author Lobo, Daniel
Malone, Taylor J.
Levin, Michael
author_facet Lobo, Daniel
Malone, Taylor J.
Levin, Michael
author_sort Lobo, Daniel
collection PubMed
description The mechanisms underlying the regenerative abilities of certain model species are of central importance to the basic understanding of pattern formation. Complex organisms such as planaria and salamanders exhibit an exceptional capacity to regenerate complete body regions and organs from amputated pieces. However, despite the outstanding bottom-up efforts of molecular biologists and bioinformatics focused at the level of gene sequence, no comprehensive mechanistic model exists that can account for more than one or two aspects of regeneration. The development of computational approaches that help scientists identify constructive models of pattern regulation is held back by the lack of both flexible morphological representations and a repository for the experimental procedures and their results (altered pattern formation). No formal representation or computational tools exist to efficiently store, search, or mine the available knowledge from regenerative experiments, inhibiting fundamental insights from this huge dataset. To overcome these problems, we present here a new class of ontology to encode formally and unambiguously a very wide range of possible morphologies, manipulations, and experiments. This formalism will pave the way for top-down approaches for the discovery of comprehensive models of regeneration. We chose the planarian regeneration dataset to illustrate a proof-of-principle of this novel bioinformatics of shape; we developed a software tool to facilitate the formalization and mining of the planarian experimental knowledge, and cured a database containing all of the experiments from the principal publications on planarian regeneration. These resources are freely available for the regeneration community and will readily assist researchers in identifying specific functional data in planarian experiments. More importantly, these applications illustrate the presented framework for formalizing knowledge about functional perturbations of morphogenesis, which is widely applicable to numerous model systems beyond regenerating planaria, and can be extended to many aspects of functional developmental, regenerative, and evolutionary biology.
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spelling pubmed-35756502013-02-21 Towards a bioinformatics of patterning: a computational approach to understanding regulative morphogenesis Lobo, Daniel Malone, Taylor J. Levin, Michael Biol Open Research Article The mechanisms underlying the regenerative abilities of certain model species are of central importance to the basic understanding of pattern formation. Complex organisms such as planaria and salamanders exhibit an exceptional capacity to regenerate complete body regions and organs from amputated pieces. However, despite the outstanding bottom-up efforts of molecular biologists and bioinformatics focused at the level of gene sequence, no comprehensive mechanistic model exists that can account for more than one or two aspects of regeneration. The development of computational approaches that help scientists identify constructive models of pattern regulation is held back by the lack of both flexible morphological representations and a repository for the experimental procedures and their results (altered pattern formation). No formal representation or computational tools exist to efficiently store, search, or mine the available knowledge from regenerative experiments, inhibiting fundamental insights from this huge dataset. To overcome these problems, we present here a new class of ontology to encode formally and unambiguously a very wide range of possible morphologies, manipulations, and experiments. This formalism will pave the way for top-down approaches for the discovery of comprehensive models of regeneration. We chose the planarian regeneration dataset to illustrate a proof-of-principle of this novel bioinformatics of shape; we developed a software tool to facilitate the formalization and mining of the planarian experimental knowledge, and cured a database containing all of the experiments from the principal publications on planarian regeneration. These resources are freely available for the regeneration community and will readily assist researchers in identifying specific functional data in planarian experiments. More importantly, these applications illustrate the presented framework for formalizing knowledge about functional perturbations of morphogenesis, which is widely applicable to numerous model systems beyond regenerating planaria, and can be extended to many aspects of functional developmental, regenerative, and evolutionary biology. The Company of Biologists 2012-11-26 /pmc/articles/PMC3575650/ /pubmed/23429669 http://dx.doi.org/10.1242/bio.20123400 Text en © 2012. Published by The Company of Biologists Ltd http://creativecommons.org/licenses/by-nc-sa/3.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial Share Alike License (http://creativecommons.org/licenses/by-nc-sa/3.0/).
spellingShingle Research Article
Lobo, Daniel
Malone, Taylor J.
Levin, Michael
Towards a bioinformatics of patterning: a computational approach to understanding regulative morphogenesis
title Towards a bioinformatics of patterning: a computational approach to understanding regulative morphogenesis
title_full Towards a bioinformatics of patterning: a computational approach to understanding regulative morphogenesis
title_fullStr Towards a bioinformatics of patterning: a computational approach to understanding regulative morphogenesis
title_full_unstemmed Towards a bioinformatics of patterning: a computational approach to understanding regulative morphogenesis
title_short Towards a bioinformatics of patterning: a computational approach to understanding regulative morphogenesis
title_sort towards a bioinformatics of patterning: a computational approach to understanding regulative morphogenesis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3575650/
https://www.ncbi.nlm.nih.gov/pubmed/23429669
http://dx.doi.org/10.1242/bio.20123400
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