Quantifying yeast colony morphologies with feature engineering from time-lapse photography

Andy Goldschmidt; James Kunert-Graf; Adrian C. Scott; Zhihao Tan; Aimée M. Dudley; J. Nathan Kutz

doi:10.1038/s41597-022-01340-3

Scientific Data (May 2022)

Quantifying yeast colony morphologies with feature engineering from time-lapse photography

Andy Goldschmidt,
James Kunert-Graf,
Adrian C. Scott,
Zhihao Tan,
Aimée M. Dudley,
J. Nathan Kutz

Affiliations

Andy Goldschmidt: Department of Physics, University of Washington
James Kunert-Graf: Pacific Northwest Research Institute
Adrian C. Scott: Pacific Northwest Research Institute
Zhihao Tan: Pacific Northwest Research Institute
Aimée M. Dudley: Pacific Northwest Research Institute
J. Nathan Kutz: Department of Applied Mathematics, University of Washington

DOI: https://doi.org/10.1038/s41597-022-01340-3
Journal volume & issue: Vol. 9, no. 1
pp. 1 – 9

Abstract

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Measurement(s) Yeast colony morphology Technology Type(s) Time-lapse photographs Factor Type(s) Genotype Sample Characteristic - Organism Saccharomyces cerevisiae

Published in Scientific Data

ISSN: 2052-4463 (Online)
Publisher: Nature Portfolio
Country of publisher: United Kingdom
LCC subjects: Science
Website: https://www.nature.com/sdata/

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