Open Accesssparse-growth-curve: a Computational Pipeline for Parsing Cellular Growth Curves with Low Temporal Resolution
Author(s) -
Chuankai Cheng,
J. Cameron Thrash
Publication year - 2021
Publication title -
microbiology resource announcements
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.383
H-Index - 35
ISSN - 2576-098X
DOI - 10.1128/mra.00296-21
Subject(s) - python (programming language) , parsing , computer science , exponential growth , software , pipeline (software) , exponential function , r package , growth curve (statistics) , curve fitting , algorithm , computational science , artificial intelligence , programming language , mathematics , machine learning , statistics , mathematical analysis
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.