| 1. |
- Chenouard, Nicolas, et al.
(author)
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Objective comparison of particle tracking methods
- 2014
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In: Nature Methods. - : Springer Science and Business Media LLC. - 1548-7091 .- 1548-7105. ; 11:3, s. 281-U247
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Journal article (peer-reviewed)abstract
- Particle tracking is of key importance for quantitative analysis of intracellular dynamic processes from time-lapse microscopy image data. Because manually detecting and following large numbers of individual particles is not feasible, automated computational methods have been developed for these tasks by many groups. Aiming to perform an objective comparison of methods, we gathered the community and organized an open competition in which participating teams applied their own methods independently to a commonly defined data set including diverse scenarios. Performance was assessed using commonly defined measures. Although no single method performed best across all scenarios, the results revealed clear differences between the various approaches, leading to notable practical conclusions for users and developers.
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| 2. |
- Cimini, Beth A, et al.
(author)
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The NEUBIAS Gateway : A hub for bioimage analysis methods and materials.
- 2020
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In: F1000Research. - : F1000 Research Ltd. - 2046-1402.
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Other publication (other academic/artistic)abstract
- We introduce the NEUBIAS Gateway, a new platform for publishing materials related to bioimage analysis, an interdisciplinary field bridging computer science and life sciences. This emerging field has been lacking a central place to share the efforts of the growing group of scientists addressing biological questions using image data. The Gateway welcomes a wide range of publication formats including articles, reviews, reports and training materials. We hope the Gateway further supports this important field to grow and helps more biologists and computational scientists learn about and contribute to these efforts.
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| 3. |
- Martins, Gabriel G., et al.
(author)
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Highlights from the 2016-2020 NEUBIAS training schools for Bioimage Analysts : a success story and key asset for analysts and life scientists
- 2021
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In: F1000 Research. - : F1000 Research Ltd. - 2046-1402. ; 10, s. 334-334
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Journal article (peer-reviewed)abstract
- NEUBIAS, the European Network of Bioimage Analysts, was created in 2016 with the goal of improving the communication and the knowledge transfer among the various stakeholders involved in the acquisition, processing and analysis of biological image data, and to promote the establishment and recognition of the profession of Bioimage Analyst. One of the most successful initiatives of the NEUBIAS programme was its series of 15 training schools, which trained over 400 new Bioimage Analysts, coming from over 40 countries. Here we outline the rationale behind the innovative three-level program of the schools, the curriculum, the trainer recruitment and turnover strategy, the outcomes for the community and the career path of analysts, including some success stories. We discuss the future of the materials created during this programme and some of the new initiatives emanating from the community of NEUBIAS-trained analysts, such as the NEUBIAS Academy. Overall, we elaborate on how this training programme played a key role in collectively leveraging Bioimaging and Life Science research by bringing the latest innovations into structured, frequent and intensive training activities, and on why we believe this should become a model to further develop in Life Sciences.
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| 4. |
- Paul-Gilloteaux, Perrine, et al.
(author)
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Bioimage analysis workflows: community resources to navigate through a complex ecosystem
- 2021
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In: F1000 Research. - : F1000 Research Ltd. - 2046-1402. ; 10, s. 320-320
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Journal article (other academic/artistic)abstract
- Workflows are the keystone of bioimage analysis, and the NEUBIAS (Network of European BioImage AnalystS) community is trying to gather the actors of this field and organize the information around them. One of its most recent outputs is the opening of the F1000Research NEUBIAS gateway, whose main objective is to offer a channel of publication for bioimage analysis workflows and associated resources. In this paper we want to express some personal opinions and recommendations related to finding, handling and developing bioimage analysis workflows. The emergence of "big data” in bioimaging and resource-intensive analysis algorithms make local data storage and computing solutions a limiting factor. At the same time, the need for data sharing with collaborators and a general shift towards remote work, have created new challenges and avenues for the execution and sharing of bioimage analysis workflows.These challenges are to reproducibly run workflows in remote environments, in particular when their components come from different software packages, but also to document them and link their parameters and results by following the FAIR principles (Findable, Accessible, Interoperable, Reusable) to foster open and reproducible science.In this opinion paper, we focus on giving some directions to the reader to tackle these challenges and navigate through this complex ecosystem, in order to find and use workflows, and to compare workflows addressing the same problem. We also discuss tools to run workflows in the cloud and on High Performance Computing resources, and suggest ways to make these workflows FAIR.
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| 5. |
- Rubens, Ulysse, et al.
(author)
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BIAFLOWS : A Collaborative Framework to Reproducibly Deploy and Benchmark Bioimage Analysis Workflows.
- 2020
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In: Patterns (New York, N.Y.). - : Elsevier BV. - 2666-3899. ; 1:3
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Journal article (peer-reviewed)abstract
- Image analysis is key to extracting quantitative information from scientific microscopy images, but the methods involved are now often so refined that they can no longer be unambiguously described by written protocols. We introduce BIAFLOWS, an open-source web tool enabling to reproducibly deploy and benchmark bioimage analysis workflows coming from any software ecosystem. A curated instance of BIAFLOWS populated with 34 image analysis workflows and 15 microscopy image datasets recapitulating common bioimage analysis problems is available online. The workflows can be launched and assessed remotely by comparing their performance visually and according to standard benchmark metrics. We illustrated these features by comparing seven nuclei segmentation workflows, including deep-learning methods. BIAFLOWS enables to benchmark and share bioimage analysis workflows, hence safeguarding research results and promoting high-quality standards in image analysis. The platform is thoroughly documented and ready to gather annotated microscopy datasets and workflows contributed by the bioimaging community.
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| 6. |
- Sladoje, Natasa, et al.
(author)
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Computer-assisted analysis of multimodal image data—perspectives and conclusion
- 2021
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In: Imaging Modalities for Biological and Preclinical Research. - : Institute of Physics Publishing (IOPP). - 9780750337472 - 9780750337458 ; , s. III.4.g-1-III.4.g-10
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Book chapter (other academic/artistic)abstract
- In this chapter, we give a general view on computer assisted image processing in a multimodal context. We discuss the main challenges of the field, some popular approaches in addressing these challenges, and ongoing community efforts to facilitate communication, collaboration, and knowledge exchange in this highly multidisciplinary, and rapidly developing field.
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