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Oufti: an integrated software package for high-accuracy, high-throughput quantitative microscopy analysis
Yale Univ, Microbial Sci Inst, West Haven, CT 06516 USA.;Yale Univ, Howard Hughes Med Inst, New Haven, CT 06520 USA..
Yale Univ, Microbial Sci Inst, West Haven, CT 06516 USA.;Yale Univ, Howard Hughes Med Inst, New Haven, CT 06520 USA.;Yale Univ, Dept Mol Cellular & Dev Biol, New Haven, CT 06520 USA..
Yale Univ, Microbial Sci Inst, West Haven, CT 06516 USA.;Yale Univ, Howard Hughes Med Inst, New Haven, CT 06520 USA.;Yale Univ, Dept Mol Cellular & Dev Biol, New Haven, CT 06520 USA..
Yale Univ, Microbial Sci Inst, West Haven, CT 06516 USA.;Yale Univ, Howard Hughes Med Inst, New Haven, CT 06520 USA.;Yale Univ, Dept Mol Cellular & Dev Biol, New Haven, CT 06520 USA..
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2016 (English)In: Molecular Microbiology, ISSN 0950-382X, E-ISSN 1365-2958, Vol. 99, no 4, 767-777 p.Article in journal (Refereed) Published
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Abstract [en]

With the realization that bacteria display phenotypic variability among cells and exhibit complex subcellular organization critical for cellular function and behavior, microscopy has re-emerged as a primary tool in bacterial research during the last decade. However, the bottleneck in today's single-cell studies is quantitative image analysis of cells and fluorescent signals. Here, we address current limitations through the development of Oufti, a stand-alone, open-source software package for automated measurements of microbial cells and fluorescence signals from microscopy images. Oufti provides computational solutions for tracking touching cells in confluent samples, handles various cell morphologies, offers algorithms for quantitative analysis of both diffraction and non-diffraction-limited fluorescence signals and is scalable for high-throughput analysis of massive datasets, all with subpixel precision. All functionalities are integrated in a single package. The graphical user interface, which includes interactive modules for segmentation, image analysis and post-processing analysis, makes the software broadly accessible to users irrespective of their computational skills.

Place, publisher, year, edition, pages
2016. Vol. 99, no 4, 767-777 p.
National Category
Medical Biotechnology (with a focus on Cell Biology (including Stem Cell Biology), Molecular Biology, Microbiology, Biochemistry or Biopharmacy)
Identifiers
URN: urn:nbn:se:uu:diva-281968DOI: 10.1111/mmi.13264ISI: 000370338900011PubMedID: 26538279OAI: oai:DiVA.org:uu-281968DiVA: diva2:916212
Funder
NIH (National Institute of Health), R01 GM065835
Available from: 2016-04-01 Created: 2016-04-01 Last updated: 2017-11-30Bibliographically approved

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Elf, Johan

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