Abstract
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.
Original language | English |
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Article number | e4681 |
Number of pages | 8 |
Journal | PeerJ |
Volume | 6 |
DOIs | |
Publication status | Published - 19 Apr 2018 |
Externally published | Yes |
Bibliographical note
This is an open access article distributed under the terms of the Creative Commons Attribution License [CC BY], 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.Keywords
- Bacteria phenotype
- Bacterial growth
- Phenotype microarrays