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Embracing Green Computing in Molecular Phylogenetics
Molecular evolutionary analyses require computationally intensive steps such as aligning multiple sequences, optimizing substitution models, inferring evolutionary trees, testing phylogenies by bootstrap analysis, and estimating divergence times. With the rise of large genomic data sets, phylogenomi...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Oxford University Press
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8894743/ https://www.ncbi.nlm.nih.gov/pubmed/35243506 http://dx.doi.org/10.1093/molbev/msac043 |
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author | Kumar, Sudhir |
author_facet | Kumar, Sudhir |
author_sort | Kumar, Sudhir |
collection | PubMed |
description | Molecular evolutionary analyses require computationally intensive steps such as aligning multiple sequences, optimizing substitution models, inferring evolutionary trees, testing phylogenies by bootstrap analysis, and estimating divergence times. With the rise of large genomic data sets, phylogenomics is imposing a big carbon footprint on the environment with consequences for the planet’s health. Electronic waste and energy usage are large environmental issues. Fortunately, innovative methods and heuristics are available to shrink the carbon footprint, presenting researchers with opportunities to lower the environmental costs and greener evolutionary computing. Green computing will also enable greater scientific rigor and encourage broader participation in big data analytics. |
format | Online Article Text |
id | pubmed-8894743 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-88947432022-03-07 Embracing Green Computing in Molecular Phylogenetics Kumar, Sudhir Mol Biol Evol Perspective Molecular evolutionary analyses require computationally intensive steps such as aligning multiple sequences, optimizing substitution models, inferring evolutionary trees, testing phylogenies by bootstrap analysis, and estimating divergence times. With the rise of large genomic data sets, phylogenomics is imposing a big carbon footprint on the environment with consequences for the planet’s health. Electronic waste and energy usage are large environmental issues. Fortunately, innovative methods and heuristics are available to shrink the carbon footprint, presenting researchers with opportunities to lower the environmental costs and greener evolutionary computing. Green computing will also enable greater scientific rigor and encourage broader participation in big data analytics. Oxford University Press 2022-03-04 /pmc/articles/PMC8894743/ /pubmed/35243506 http://dx.doi.org/10.1093/molbev/msac043 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Perspective Kumar, Sudhir Embracing Green Computing in Molecular Phylogenetics |
title | Embracing Green Computing in Molecular Phylogenetics |
title_full | Embracing Green Computing in Molecular Phylogenetics |
title_fullStr | Embracing Green Computing in Molecular Phylogenetics |
title_full_unstemmed | Embracing Green Computing in Molecular Phylogenetics |
title_short | Embracing Green Computing in Molecular Phylogenetics |
title_sort | embracing green computing in molecular phylogenetics |
topic | Perspective |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8894743/ https://www.ncbi.nlm.nih.gov/pubmed/35243506 http://dx.doi.org/10.1093/molbev/msac043 |
work_keys_str_mv | AT kumarsudhir embracinggreencomputinginmolecularphylogenetics |