دورية أكاديمية
NODeJ: an ImageJ plugin for 3D segmentation of nuclear objects
| العنوان: | NODeJ: an ImageJ plugin for 3D segmentation of nuclear objects |
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| المؤلفون: | Tristan Dubos, Axel Poulet, Geoffrey Thomson, Emilie Péry, Frédéric Chausse, Christophe Tatout, Sophie Desset, Josien C. van Wolfswinkel, Yannick Jacob |
| المصدر: | BMC Bioinformatics, Vol 23, Iss 1, Pp 1-11 (2022) |
| بيانات النشر: | BMC, 2022. |
| سنة النشر: | 2022 |
| المجموعة: | LCC:Computer applications to medicine. Medical informatics LCC:Biology (General) |
| مصطلحات موضوعية: | Heterochromatin organization, Chromocenter, 3D image analysis, 3D DNA FISH analysis, Computer applications to medicine. Medical informatics, R858-859.7, Biology (General), QH301-705.5 |
| الوصف: | Abstract Background The three-dimensional nuclear arrangement of chromatin impacts many cellular processes operating at the DNA level in animal and plant systems. Chromatin organization is a dynamic process that can be affected by biotic and abiotic stresses. Three-dimensional imaging technology allows to follow these dynamic changes, but only a few semi-automated processing methods currently exist for quantitative analysis of the 3D chromatin organization. Results We present an automated method, Nuclear Object DetectionJ (NODeJ), developed as an imageJ plugin. This program segments and analyzes high intensity domains in nuclei from 3D images. NODeJ performs a Laplacian convolution on the mask of a nucleus to enhance the contrast of intra-nuclear objects and allow their detection. We reanalyzed public datasets and determined that NODeJ is able to accurately identify heterochromatin domains from a diverse set of Arabidopsis thaliana nuclei stained with DAPI or Hoechst. NODeJ is also able to detect signals in nuclei from DNA FISH experiments, allowing for the analysis of specific targets of interest. Conclusion and availability NODeJ allows for efficient automated analysis of subnuclear structures by avoiding the semi-automated steps, resulting in reduced processing time and analytical bias. NODeJ is written in Java and provided as an ImageJ plugin with a command line option to perform more high-throughput analyses. NODeJ can be downloaded from https://gitlab.com/axpoulet/image2danalysis/-/releasesTest with source code, documentation and further information avaliable at https://gitlab.com/axpoulet/image2danalysisTest . The images used in this study are publicly available at https://www.brookes.ac.uk/indepth/imagesTest/ and https://doi.org/10.15454/1HSOIETest . |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 1471-2105 |
| العلاقة: | https://doaj.org/toc/1471-2105Test |
| DOI: | 10.1186/s12859-022-04743-6 |
| الوصول الحر: | https://doaj.org/article/5b8249155f3d449fbb5660f4903a251dTest |
| رقم الانضمام: | edsdoj.5b8249155f3d449fbb5660f4903a251d |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 14712105 |
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| DOI: | 10.1186/s12859-022-04743-6 |