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TAMMiCol: Tool for analysis of the morphology of microbial colonies.
Tronnolone, Hayden; Gardner, Jennifer M; Sundstrom, Joanna F; Jiranek, Vladimir; Oliver, Stephen G; Binder, Benjamin J.
Afiliação
  • Tronnolone H; School of Mathematical Sciences, University of Adelaide, Adelaide, Australia.
  • Gardner JM; Department of Wine and Food Science, University of Adelaide, Adelaide, Australia.
  • Sundstrom JF; Department of Wine and Food Science, University of Adelaide, Adelaide, Australia.
  • Jiranek V; Department of Wine and Food Science, University of Adelaide, Adelaide, Australia.
  • Oliver SG; Cambridge Systems Biology Centre and Department of Biochemistry, University of Cambridge, Cambridge, United Kingdom.
  • Binder BJ; School of Mathematical Sciences, University of Adelaide, Adelaide, Australia.
PLoS Comput Biol ; 14(12): e1006629, 2018 12.
Article em En | MEDLINE | ID: mdl-30507938
Many microbes are studied by examining colony morphology via two-dimensional top-down images. The quantification of such images typically requires each pixel to be labelled as belonging to either the colony or background, producing a binary image. While this may be achieved manually for a single colony, this process is infeasible for large datasets containing thousands of images. The software Tool for Analysis of the Morphology of Microbial Colonies (TAMMiCol) has been developed to efficiently and automatically convert colony images to binary. TAMMiCol exploits the structure of the images to choose a thresholding tolerance and produce a binary image of the colony. The images produced are shown to compare favourably with images processed manually, while TAMMiCol is shown to outperform standard segmentation methods. Multiple images may be imported together for batch processing, while the binary data may be exported as a CSV or MATLAB MAT file for quantification, or analysed using statistics built into the software. Using the in-built statistics, it is found that images produced by TAMMiCol yield values close to those computed from binary images processed manually. Analysis of a new large dataset using TAMMiCol shows that colonies of Saccharomyces cerevisiae reach a maximum level of filamentous growth once the concentration of ammonium sulfate is reduced to 200 µM. TAMMiCol is accessed through a graphical user interface, making it easy to use for those without specialist knowledge of image processing, statistical methods or coding.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Processamento de Imagem Assistida por Computador / Software / Microbiota Idioma: En Revista: PLoS Comput Biol Assunto da revista: BIOLOGIA / INFORMATICA MEDICA Ano de publicação: 2018 Tipo de documento: Article País de afiliação: Austrália

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Processamento de Imagem Assistida por Computador / Software / Microbiota Idioma: En Revista: PLoS Comput Biol Assunto da revista: BIOLOGIA / INFORMATICA MEDICA Ano de publicação: 2018 Tipo de documento: Article País de afiliação: Austrália