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A unifying framework for fast randomization of ecological networks with fixed (node) degrees
The Curveball algorithm is an efficient and unbiased procedure for randomizing bipartite networks (or their matrix counterpart) while preserving node degrees. Here we introduce two extensions of the procedure, making it capable to randomize also unimode directed and undirected networks. We provide f...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6072652/ https://www.ncbi.nlm.nih.gov/pubmed/30094204 http://dx.doi.org/10.1016/j.mex.2018.06.018 |
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author | Carstens, Corrie Jacobien Berger, Annabell Strona, Giovanni |
author_facet | Carstens, Corrie Jacobien Berger, Annabell Strona, Giovanni |
author_sort | Carstens, Corrie Jacobien |
collection | PubMed |
description | The Curveball algorithm is an efficient and unbiased procedure for randomizing bipartite networks (or their matrix counterpart) while preserving node degrees. Here we introduce two extensions of the procedure, making it capable to randomize also unimode directed and undirected networks. We provide formal mathematical proofs that the two extensions, as the original Curveball, are fast and unbiased (i.e. they sample uniformly from the universe of possible network configurations). • We extend the Curveball algorithm to unimode directed and undirected networks. • As the original Curveball, extensions are fast and unbiased. • We provide Python and R code implementing the new procedures. |
format | Online Article Text |
id | pubmed-6072652 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-60726522018-08-09 A unifying framework for fast randomization of ecological networks with fixed (node) degrees Carstens, Corrie Jacobien Berger, Annabell Strona, Giovanni MethodsX Agricultural and Biological Science The Curveball algorithm is an efficient and unbiased procedure for randomizing bipartite networks (or their matrix counterpart) while preserving node degrees. Here we introduce two extensions of the procedure, making it capable to randomize also unimode directed and undirected networks. We provide formal mathematical proofs that the two extensions, as the original Curveball, are fast and unbiased (i.e. they sample uniformly from the universe of possible network configurations). • We extend the Curveball algorithm to unimode directed and undirected networks. • As the original Curveball, extensions are fast and unbiased. • We provide Python and R code implementing the new procedures. Elsevier 2018-07-05 /pmc/articles/PMC6072652/ /pubmed/30094204 http://dx.doi.org/10.1016/j.mex.2018.06.018 Text en © 2018 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Agricultural and Biological Science Carstens, Corrie Jacobien Berger, Annabell Strona, Giovanni A unifying framework for fast randomization of ecological networks with fixed (node) degrees |
title | A unifying framework for fast randomization of ecological networks with fixed (node) degrees |
title_full | A unifying framework for fast randomization of ecological networks with fixed (node) degrees |
title_fullStr | A unifying framework for fast randomization of ecological networks with fixed (node) degrees |
title_full_unstemmed | A unifying framework for fast randomization of ecological networks with fixed (node) degrees |
title_short | A unifying framework for fast randomization of ecological networks with fixed (node) degrees |
title_sort | unifying framework for fast randomization of ecological networks with fixed (node) degrees |
topic | Agricultural and Biological Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6072652/ https://www.ncbi.nlm.nih.gov/pubmed/30094204 http://dx.doi.org/10.1016/j.mex.2018.06.018 |
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