Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/117321
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Type: | Journal article |
Title: | Characterizing the shape patterns of dimorphic yeast pseudohyphae |
Author: | Gontar, A. Bottema, M.J. Binder, B.J. Tronnolone, H. |
Citation: | Royal Society Open Science, 2018; 5(10):180820-1-180820-12 |
Publisher: | Royal Society |
Issue Date: | 2018 |
ISSN: | 2054-5703 2054-5703 |
Statement of Responsibility: | Amelia Gontar, Murk J. Bottema, Benjamin J. Binder and Hayden Tronnolone |
Abstract: | Pseudohyphal growth of the dimorphic yeast Saccharomyces cerevisiae is analysed using two-dimensional top-down binary images. The colony morphology is characterized using clustered shape primitives (CSPs), which are learned automatically from the data and thus do not require a list of predefined features or a priori knowledge of the shape. The power of CSPs is demonstrated through the classification of pseudohyphal yeast colonies known to produce different morphologies. The classifier categorizes the yeast colonies considered with an accuracy of 0.969 and standard deviation 0.041, demonstrating that CSPs capture differences in morphology, while CSPs are found to provide greater discriminatory power than spatial indices previously used to quantify pseudohyphal growth. The analysis demonstrates that CSPs provide a promising avenue for analysing morphology in high-throughput assays. |
Keywords: | Clustered shape primitives dimorphic yeast pseudohyphal growth shape characterization |
Rights: | © 2018 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited. |
DOI: | 10.1098/rsos.180820 |
Grant ID: | http://purl.org/au-research/grants/arc/DP160102644 |
Published version: | http://dx.doi.org/10.1098/rsos.180820 |
Appears in Collections: | Aurora harvest 3 Mathematical Sciences publications |
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hdl_117321.pdf | Published version | 747.61 kB | Adobe PDF | View/Open |
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