OMERO: flexible, model-driven data management for experimental biology

Allan, Chris; Burel, Jean‐Marie; Moore, Josh; Blackburn, Colin; Linkert, Melissa; Loynton, Scott; MacDonald, Donald; Moore, William J.; Neves, Carlos; Patterson, Andrew; Porter, Michael; Tarkowska, Aleksandra; Loranger, Brian; Avondo, Jerome; Lagerstedt, Ingvar; Lianas, Luca; Leo, Simone; Hands, Katherine J.; Hay, Ronald T.; Patwardhan, Ardan; Best, C.; Kleywegt, Gerard J.; Zanetti, Gianluigi; Swedlow, Jason R.

doi:10.1038/nmeth.1896

Cited by 528 publications

(449 citation statements)

References 18 publications

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“…By designing workflow arrangements via an intuitive graphical user interface, both expert and non‐expert users gain access to automated image and data analysis solutions. The strength of such a platform or other tools like OMERO (Open Microcopy Environment Remote Objects, (Allan et al, 2012) [20]) and BISQUE (Bio‐Image Semantic Query User Environment, (Kvilekval et al, 2010) [21]) is that they are separated from the software pieces that actually do the work.…”

Section: Data Analysis and Data Managementmentioning

confidence: 99%

Advanced light microscopy core facilities: Balancing service, science and career

Ferrando‐May

Hartmann

Reymann

et al. 2016

Microsc. Res. Tech.

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Core Facilities (CF) for advanced light microscopy (ALM) have become indispensable support units for research in the life sciences. Their organizational structure and technical characteristics are quite diverse, although the tasks they pursue and the services they offer are similar. Therefore, throughout Europe, scientists from ALM‐CFs are forming networks to promote interactions and discuss best practice models. Here, we present recommendations for ALM‐CF operations elaborated by the workgroups of the German network of ALM‐CFs, German Bio‐Imaging (GerBI). We address technical aspects of CF planning and instrument maintainance, give advice on the organization and management of an ALM‐CF, propose a scheme for the training of CF users, and provide an overview of current resources for image processing and analysis. Further, we elaborate on the new challenges and opportunities for professional development and careers created by CFs. While some information specifically refers to the German academic system, most of the content of this article is of general interest for CFs in the life sciences. Microsc. Res. Tech. 79:463–479, 2016. © 2016 THE AUTHORS MICROSCOPY RESEARCH AND TECHNIQUE PUBLISHED BY WILEY PERIODICALS, INC.

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Section: Data Analysis and Data Managementmentioning

confidence: 99%

Advanced light microscopy core facilities: Balancing service, science and career

Ferrando‐May

Hartmann

Reymann

et al. 2016

Microsc. Res. Tech.

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“…Fiji was used for image analysis [57] and MATLAB for data processing using a custom written script (provided as Supplementary material). Time-lapse figures were created with OMERO.figure [58]. …”

Section: Methodsmentioning

confidence: 99%

Simultaneous dual-channel imaging to quantify interdependent protein recruitment to laser-induced DNA damage sites

Garbrecht

Hornegger

Herbert

et al. 2018

Nucleus

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Fluorescence microscopy in combination with the induction of localized DNA damage using focused light beams has played a major role in the study of protein recruitment kinetics to DNA damage sites in recent years. Currently published methods are dedicated to the study of single fluorophore/single protein kinetics. However, these methods may be limited when studying the relative recruitment dynamics between two or more proteins due to cell-to-cell variability in gene expression and recruitment kinetics, and are not suitable for comparative analysis of fast-recruiting proteins. To tackle these limitations, we have established a time-lapse fluorescence microscopy method based on simultaneous dual-channel acquisition following UV-A-induced local DNA damage coupled with a standardized image and recruitment analysis workflow. Simultaneous acquisition is achieved by spectrally splitting the emitted light into two light paths, which are simultaneously imaged on two halves of the same camera chip. To validate this method, we studied the recruitment of poly(ADP-ribose) polymerase 1 (PARP1), poly (ADP-ribose) glycohydrolase (PARG), proliferating cell nuclear antigen (PCNA) and the chromatin remodeler ALC1. In accordance with the published data based on single fluorophore imaging, simultaneous dual-channel imaging revealed that PARP1 regulates fast recruitment and dissociation of PARG and that in PARP1-depleted cells PARG and PCNA are recruited with comparable kinetics. This approach is particularly advantageous for analyzing the recruitment sequence of fast-recruiting proteins such as PARP1 and ALC1, and revealed that PARP1 is recruited faster than ALC1. Split-view imaging can be incorporated into any laser microirradiation-adapted microscopy setup together with a recruitment-dedicated image analysis package.

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“…In plant sciences this can encompass anything from the canopies of forests to the colocalisation of protein signals within leaf cells. Many bioimage informatics tools are, of course, transferable across all of the biological sciences, such examples include the Open Microscopy Environment Remote Objects (OMERO; Allan et al 2012) and Bio-Image Semantic Query User Environment (Bisque; Kvilekval et al 2010) platforms, an open-source management and access software for a wide range of biological data. Indeed new features are being developed that add functionality to such systems, for example (Cho et al 2012).…”

Section: Bioimage Informatics In the Plant Sciencesmentioning

confidence: 99%

Blobs and curves: object-based colocalisation for plant cells

Nelson

Duckney

Hawkins

et al. 2015

Functional Plant Biol.

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Quantifying the colocalisation of labels is a major application of fluorescent microscopy in plant biology. Pixel-based, i.e. Pearson's coefficient, quantification of colocalisation is a limited tool that gives limited information for further analysis. We show how applying bioimage informatics tools to a commonplace experiment allows further quantifiable results to be extracted. We use our object-based colocalisation technique to extract distance information, show temporal changes and demonstrate the advantages, and pitfalls, of using bioimage informatics for plant science.

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OMERO: flexible, model-driven data management for experimental biology

Cited by 528 publications

References 18 publications

Advanced light microscopy core facilities: Balancing service, science and career

Advanced light microscopy core facilities: Balancing service, science and career

Simultaneous dual-channel imaging to quantify interdependent protein recruitment to laser-induced DNA damage sites

Blobs and curves: object-based colocalisation for plant cells

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