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PLoS Computational Biology Issue Image | Vol. 15(10) October 2019

PLoS Computational Biology Issue Image | Vol. 15(10) October 2019

PLOS
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Image analysis to characterize fungal growth and morphology

Fungi produce complex networks of filamentous structures that allow them to colonize different environments. The filamentous nature makes quantitative analyses of fungal growth dynamics and morphology challenging. Vidal-Diez de Ulzurrun et al. have developed a new method for capturing images of live fungi and a tool, Fungal Feature Tracker, to extract different morphological features from fungal images. FFT can quantitatively characterize fungal morphology, cell number and measure filamentous growth allowing objective and precise characterization of phenotypes which will advance our understanding of fungal growth and biology.

Image Credit: Guillermo Vidal-Diez de Ulzurrun, Institute of Molecular Biology, Academia Sinica, Taiwan

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Image analysis to characterize fungal growth and morphology

Fungi produce complex networks of filamentous structures that allow them to colonize different environments. The filamentous nature makes quantitative analyses of fungal growth dynamics and morphology challenging. Vidal-Diez de Ulzurrun et al. have developed a new method for capturing images of live fungi and a tool, Fungal Feature Tracker, to extract different morphological features from fungal images. FFT can quantitatively characterize fungal morphology, cell number and measure filamentous growth allowing objective and precise characterization of phenotypes which will advance our understanding of fungal growth and biology.

Image Credit: Guillermo Vidal-Diez de Ulzurrun, Institute of Molecular Biology, Academia Sinica, Taiwan

https://doi.org/10.1371/image.pcbi.v15.i10.g001