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Transferable Measurements of Heredity in Models of the Origins of Life
We propose a metric which can be used to compute the amount of heritable variation enabled by a given dynamical system. A distribution of selection pressures is used such that each pressure selects a particular fixed point via competitive exclusion in order to determine the corresponding distributio...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4610668/ https://www.ncbi.nlm.nih.gov/pubmed/26480478 http://dx.doi.org/10.1371/journal.pone.0140663 |
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author | Guttenberg, Nicholas Laneuville, Matthieu Ilardo, Melissa Aubert-Kato, Nathanael |
author_facet | Guttenberg, Nicholas Laneuville, Matthieu Ilardo, Melissa Aubert-Kato, Nathanael |
author_sort | Guttenberg, Nicholas |
collection | PubMed |
description | We propose a metric which can be used to compute the amount of heritable variation enabled by a given dynamical system. A distribution of selection pressures is used such that each pressure selects a particular fixed point via competitive exclusion in order to determine the corresponding distribution of potential fixed points in the population dynamics. This metric accurately detects the number of species present in artificially prepared test systems, and furthermore can correctly determine the number of heritable sets in clustered transition matrix models in which there are no clearly defined genomes. Finally, we apply our metric to the GARD model and show that it accurately reproduces prior measurements of the model’s heritability. |
format | Online Article Text |
id | pubmed-4610668 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-46106682015-10-29 Transferable Measurements of Heredity in Models of the Origins of Life Guttenberg, Nicholas Laneuville, Matthieu Ilardo, Melissa Aubert-Kato, Nathanael PLoS One Research Article We propose a metric which can be used to compute the amount of heritable variation enabled by a given dynamical system. A distribution of selection pressures is used such that each pressure selects a particular fixed point via competitive exclusion in order to determine the corresponding distribution of potential fixed points in the population dynamics. This metric accurately detects the number of species present in artificially prepared test systems, and furthermore can correctly determine the number of heritable sets in clustered transition matrix models in which there are no clearly defined genomes. Finally, we apply our metric to the GARD model and show that it accurately reproduces prior measurements of the model’s heritability. Public Library of Science 2015-10-19 /pmc/articles/PMC4610668/ /pubmed/26480478 http://dx.doi.org/10.1371/journal.pone.0140663 Text en © 2015 Guttenberg et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Guttenberg, Nicholas Laneuville, Matthieu Ilardo, Melissa Aubert-Kato, Nathanael Transferable Measurements of Heredity in Models of the Origins of Life |
title | Transferable Measurements of Heredity in Models of the Origins of Life |
title_full | Transferable Measurements of Heredity in Models of the Origins of Life |
title_fullStr | Transferable Measurements of Heredity in Models of the Origins of Life |
title_full_unstemmed | Transferable Measurements of Heredity in Models of the Origins of Life |
title_short | Transferable Measurements of Heredity in Models of the Origins of Life |
title_sort | transferable measurements of heredity in models of the origins of life |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4610668/ https://www.ncbi.nlm.nih.gov/pubmed/26480478 http://dx.doi.org/10.1371/journal.pone.0140663 |
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