sparse-growth-curve: a Computational Pipeline for Parsing Cellular Growth Curves with Low Temporal Resolution

Here, we introduce a Python-based repository, sparse-growth-curve, a software package designed for parsing cellular growth curves with low temporal resolution. The repository uses cell density and time data as the input, automatically separates different growth phases, calculates the exponential gro...

Descripción completa

Detalles Bibliográficos
Autores principales: Cheng, Chuankai, Thrash, J. Cameron
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Society for Microbiology 2021
Materias:
Databases and Software
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8142577/
https://www.ncbi.nlm.nih.gov/pubmed/33986091
http://dx.doi.org/10.1128/MRA.00296-21
_version_ 1783696581683314688
author Cheng, Chuankai
Thrash, J. Cameron
author_facet Cheng, Chuankai
Thrash, J. Cameron
author_sort Cheng, Chuankai
collection PubMed
description Here, we introduce a Python-based repository, sparse-growth-curve, a software package designed for parsing cellular growth curves with low temporal resolution. The repository uses cell density and time data as the input, automatically separates different growth phases, calculates the exponential growth rates, and produces multiple graphs to aid in interpretation.
format Online
Article
Text
id pubmed-8142577
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher American Society for Microbiology
record_format MEDLINE/PubMed
spelling pubmed-81425772021-06-14 sparse-growth-curve: a Computational Pipeline for Parsing Cellular Growth Curves with Low Temporal Resolution Cheng, Chuankai Thrash, J. Cameron Microbiol Resour Announc Databases and Software Here, we introduce a Python-based repository, sparse-growth-curve, a software package designed for parsing cellular growth curves with low temporal resolution. The repository uses cell density and time data as the input, automatically separates different growth phases, calculates the exponential growth rates, and produces multiple graphs to aid in interpretation. American Society for Microbiology 2021-05-13 /pmc/articles/PMC8142577/ /pubmed/33986091 http://dx.doi.org/10.1128/MRA.00296-21 Text en Copyright © 2021 Cheng and Thrash. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Databases and Software
Cheng, Chuankai
Thrash, J. Cameron
sparse-growth-curve: a Computational Pipeline for Parsing Cellular Growth Curves with Low Temporal Resolution
title sparse-growth-curve: a Computational Pipeline for Parsing Cellular Growth Curves with Low Temporal Resolution
title_full sparse-growth-curve: a Computational Pipeline for Parsing Cellular Growth Curves with Low Temporal Resolution
title_fullStr sparse-growth-curve: a Computational Pipeline for Parsing Cellular Growth Curves with Low Temporal Resolution
title_full_unstemmed sparse-growth-curve: a Computational Pipeline for Parsing Cellular Growth Curves with Low Temporal Resolution
title_short sparse-growth-curve: a Computational Pipeline for Parsing Cellular Growth Curves with Low Temporal Resolution
title_sort sparse-growth-curve: a computational pipeline for parsing cellular growth curves with low temporal resolution
topic Databases and Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8142577/
https://www.ncbi.nlm.nih.gov/pubmed/33986091
http://dx.doi.org/10.1128/MRA.00296-21
work_keys_str_mv AT chengchuankai sparsegrowthcurveacomputationalpipelineforparsingcellulargrowthcurveswithlowtemporalresolution
AT thrashjcameron sparsegrowthcurveacomputationalpipelineforparsingcellulargrowthcurveswithlowtemporalresolution

Ejemplares similares