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Quantification of variability in trichome patterns
While pattern formation is studied in various areas of biology, little is known about the noise leading to variations between individual realizations of the pattern. One prominent example for de novo pattern formation in plants is the patterning of trichomes on Arabidopsis leaves, which involves gen...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4230044/ https://www.ncbi.nlm.nih.gov/pubmed/25431575 http://dx.doi.org/10.3389/fpls.2014.00596 |
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author | Greese, Bettina Hülskamp, Martin Fleck, Christian |
author_facet | Greese, Bettina Hülskamp, Martin Fleck, Christian |
author_sort | Greese, Bettina |
collection | PubMed |
description | While pattern formation is studied in various areas of biology, little is known about the noise leading to variations between individual realizations of the pattern. One prominent example for de novo pattern formation in plants is the patterning of trichomes on Arabidopsis leaves, which involves genetic regulation and cell-to-cell communication. These processes are potentially variable due to, e.g., the abundance of cell components or environmental conditions. To elevate the understanding of regulatory processes underlying the pattern formation it is crucial to quantitatively analyze the variability in naturally occurring patterns. Here, we review recent approaches toward characterization of noise on trichome initiation. We present methods for the quantification of spatial patterns, which are the basis for data-driven mathematical modeling and enable the analysis of noise from different sources. Besides the insight gained on trichome formation, the examination of observed trichome patterns also shows that highly regulated biological processes can be substantially affected by variability. |
format | Online Article Text |
id | pubmed-4230044 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-42300442014-11-27 Quantification of variability in trichome patterns Greese, Bettina Hülskamp, Martin Fleck, Christian Front Plant Sci Plant Science While pattern formation is studied in various areas of biology, little is known about the noise leading to variations between individual realizations of the pattern. One prominent example for de novo pattern formation in plants is the patterning of trichomes on Arabidopsis leaves, which involves genetic regulation and cell-to-cell communication. These processes are potentially variable due to, e.g., the abundance of cell components or environmental conditions. To elevate the understanding of regulatory processes underlying the pattern formation it is crucial to quantitatively analyze the variability in naturally occurring patterns. Here, we review recent approaches toward characterization of noise on trichome initiation. We present methods for the quantification of spatial patterns, which are the basis for data-driven mathematical modeling and enable the analysis of noise from different sources. Besides the insight gained on trichome formation, the examination of observed trichome patterns also shows that highly regulated biological processes can be substantially affected by variability. Frontiers Media S.A. 2014-11-13 /pmc/articles/PMC4230044/ /pubmed/25431575 http://dx.doi.org/10.3389/fpls.2014.00596 Text en Copyright © 2014 Greese, Hülskamp and Fleck. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Plant Science Greese, Bettina Hülskamp, Martin Fleck, Christian Quantification of variability in trichome patterns |
title | Quantification of variability in trichome patterns |
title_full | Quantification of variability in trichome patterns |
title_fullStr | Quantification of variability in trichome patterns |
title_full_unstemmed | Quantification of variability in trichome patterns |
title_short | Quantification of variability in trichome patterns |
title_sort | quantification of variability in trichome patterns |
topic | Plant Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4230044/ https://www.ncbi.nlm.nih.gov/pubmed/25431575 http://dx.doi.org/10.3389/fpls.2014.00596 |
work_keys_str_mv | AT greesebettina quantificationofvariabilityintrichomepatterns AT hulskampmartin quantificationofvariabilityintrichomepatterns AT fleckchristian quantificationofvariabilityintrichomepatterns |