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Growth Score: a single metric to define growth in 96-well phenotype assays
High-throughput phenotype assays are a cornerstone of systems biology as they allow direct measurements of mutations, genes, strains, or even different genera. High-throughput methods also require data analytic methods that reduce complex time-series data to a single numeric evaluation. Here, we pre...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5911387/ https://www.ncbi.nlm.nih.gov/pubmed/29686949 http://dx.doi.org/10.7717/peerj.4681 |
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author | Cuevas, Daniel A. Edwards, Robert A. |
author_facet | Cuevas, Daniel A. Edwards, Robert A. |
author_sort | Cuevas, Daniel A. |
collection | PubMed |
description | High-throughput phenotype assays are a cornerstone of systems biology as they allow direct measurements of mutations, genes, strains, or even different genera. High-throughput methods also require data analytic methods that reduce complex time-series data to a single numeric evaluation. Here, we present the Growth Score, an improvement on the previous Growth Level formula. There is strong correlation between Growth Score and Growth Level, but the new Growth Score contains only essential growth curve properties while the formula of the previous Growth Level was convoluted and not easily interpretable. Several programs can be used to estimate the parameters required to calculate the Growth Score metric, including our PMAnalyzer pipeline. |
format | Online Article Text |
id | pubmed-5911387 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-59113872018-04-23 Growth Score: a single metric to define growth in 96-well phenotype assays Cuevas, Daniel A. Edwards, Robert A. PeerJ Computational Biology High-throughput phenotype assays are a cornerstone of systems biology as they allow direct measurements of mutations, genes, strains, or even different genera. High-throughput methods also require data analytic methods that reduce complex time-series data to a single numeric evaluation. Here, we present the Growth Score, an improvement on the previous Growth Level formula. There is strong correlation between Growth Score and Growth Level, but the new Growth Score contains only essential growth curve properties while the formula of the previous Growth Level was convoluted and not easily interpretable. Several programs can be used to estimate the parameters required to calculate the Growth Score metric, including our PMAnalyzer pipeline. PeerJ Inc. 2018-04-19 /pmc/articles/PMC5911387/ /pubmed/29686949 http://dx.doi.org/10.7717/peerj.4681 Text en ©2018 Cuevas and Edwards http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited. |
spellingShingle | Computational Biology Cuevas, Daniel A. Edwards, Robert A. Growth Score: a single metric to define growth in 96-well phenotype assays |
title | Growth Score: a single metric to define growth in 96-well phenotype assays |
title_full | Growth Score: a single metric to define growth in 96-well phenotype assays |
title_fullStr | Growth Score: a single metric to define growth in 96-well phenotype assays |
title_full_unstemmed | Growth Score: a single metric to define growth in 96-well phenotype assays |
title_short | Growth Score: a single metric to define growth in 96-well phenotype assays |
title_sort | growth score: a single metric to define growth in 96-well phenotype assays |
topic | Computational Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5911387/ https://www.ncbi.nlm.nih.gov/pubmed/29686949 http://dx.doi.org/10.7717/peerj.4681 |
work_keys_str_mv | AT cuevasdaniela growthscoreasinglemetrictodefinegrowthin96wellphenotypeassays AT edwardsroberta growthscoreasinglemetrictodefinegrowthin96wellphenotypeassays |