Article (Scientific journals)
Quantitative analysis of colony morphology in yeast
Ruusuvuori, Pekka; Lin, Jake; Shmulevich, Ilya et al.
2013In BioTechniques
Peer reviewed
 

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Keywords :
Colony morphology; Image analysis; Software; Yeast; Phenotype; Timelapse
Abstract :
[en] Microorganisms often form multicellular structures,such as biofilms and structured colonies, which can influence the organism’s virulence, drug resistance, and adherence to medical devices. Phenotypic classification of these structures has traditionally relied on qualitative scoring systems that limit detailed phenotypic comparisons between strains. Automated imaging and quantitative analysis have the potential to improve the speed and accuracy of experiments designed to study the genetic and molecular networks underlying different morphological traits. We have developeda platform that uses automated image analysis and pattern recognition to quantify phenotypic signatures of yeast colonies. The strategy enables quantitative analysis of individual colonies, measured at a single time point or over a series of time-lapse images, as well as the classification of distinct colony shapes based on image-derived features. Phenotypic changes in colonymorphology can be expressed achanges in feature space trajectories over time, thereby enabling the visualization and quantitative analysis of morphological development. To facilitate data exploration, results are plotted dynamically through an interactive web application that integrates the raw and processed images across all time points, allowing exploration of the image-based features and principal components associated with morphological development. The web application YIMAA is available at http://yimaa.cs.tut.fi.
Research center :
- Luxembourg Centre for Systems Biomedicine (LCSB): Bioinformatics Core (R. Schneider Group)
Disciplines :
Biotechnology
Author, co-author :
Ruusuvuori, Pekka
Lin, Jake ;  University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB)
Shmulevich, Ilya
Nykter, Matti
Scott, Adrian
Tan, Zhihao
Sorsa, Saija
Dudley, Aimee
External co-authors :
yes
Language :
English
Title :
Quantitative analysis of colony morphology in yeast
Publication date :
19 November 2013
Journal title :
BioTechniques
ISSN :
0736-6205
Publisher :
Eaton Publishing Company, Natick, United States - Massachusetts
Peer reviewed :
Peer reviewed
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