ArticlePLoS computational biology2015
Quantifying two-dimensional filamentous and invasive growth spatial patterns in yeast colonies.
Article in PLoS computational biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Quantification ofJournal of the Royal Society, Interface · 2024Article
- An off-lattice discrete model to characterise filamentous yeast colony morphology.PLoS computational biology · 2024Article
- Integrative analysis of yeast colony growth.Communications biology · 2024Article
- HYPHAEdelity: a quantitative image analysis tool for assessing peripheral whole colony filamentation.FEMS yeast research · 2022Article
- TAMMiCol: Tool for analysis of the morphology of microbial colonies.PLoS computational biology · 2018Article
- Characterizing the shape patterns of dimorphic yeast pseudohyphae.Royal Society open science · 2018Article
- Diffusion-Limited Growth of Microbial Colonies.Scientific reports · 2018Article
- Quantifying the dominant growth mechanisms of dimorphic yeast using a lattice-based model.Journal of the Royal Society, Interface · 2017Article
- Identifying the necrotic zone boundary in tumour spheroids with pair-correlation functions.Journal of the Royal Society, Interface · 2016Article
Corrections and comments
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Authors and funding
5 authors.
Funding
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Abstract
The top-view, two-dimensional spatial patterning of non-uniform growth in a Saccharomyces cerevisiae yeast colony is considered. Experimental images are processed to obtain data sets that provide spatial information on the cell-area that is occupied by the colony. A method is developed that allows for the analysis of the spatial distribution with three metrics. The growth of the colony is quantified in both the radial direction from the centre of the colony and in the angular direction in a prescribed outer region of the colony. It is shown that during the period of 100-200 hours from the start of the growth of the colony there is an increasing amount of non-uniform growth. The statistical framework outlined in this work provides a platform for comparative quantitative assays of strain-specific mechanisms, with potential implementation in inferencing algorithms used for parameter-rate estimation.
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