GeNePy3D: a quantitative geometry python toolbox for bioimaging
| Autor: | Anatole Chessel, Minh-Son Phan |
|---|---|
| Přispěvatelé: | Hub d'analyse d'images - Image Analysis Hub (Platform) (IAH), Institut Pasteur [Paris] (IP)-Université Paris Cité (UPCité), Laboratoire d'Optique et Biosciences (LOB), École polytechnique (X)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), This publication was supported by COST Action NEUBIAS (CA15124), funded by COST (European Cooperation in Science andTechnology., Phan, Minh Son |
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
0301 basic medicine
Computer science workflow Framing (World Wide Web) Bioimage informatics MESH: Algorithms computer.software_genre General Biochemistry Genetics and Molecular Biology 03 medical and health sciences MESH: Software 0302 clinical medicine Image Processing Computer-Assisted computational geometry Animals MESH: Animals General Pharmacology Toxicology and Pharmaceutics MESH: Zebrafish Spatial analysis Zebrafish Geometric data analysis computer.programming_language [INFO.INFO-BI] Computer Science [cs]/Bioinformatics [q-bio.QM] General Immunology and Microbiology Application programming interface Software Tool Article Programming language quantitative geometry Reproducibility of Results Articles General Medicine Python (programming language) Computational geometry MESH: Image Processing Computer-Assisted Toolbox bioimage informatics python MESH: Reproducibility of Results 030104 developmental biology [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM] computer Algorithms Software 030217 neurology & neurosurgery |
| Zdroj: | F1000Research F1000Research, 2021, ⟨10.12688/f1000research.27395.2⟩ |
| ISSN: | 2046-1402 |
| Popis: | La date de publication correspond à la deuxième version de l'article (Première version 26 novembre 2020); International audience; The advent of large-scale fluorescence and electronic microscopy techniques along with maturing image analysis is giving life sciences a deluge of geometrical objects in 2D/3D(+t) to deal with. These objects take the form of large scale, localised, precise, single cell, quantitative data such as cells’ positions, shapes, trajectories or lineages, axon traces in whole brains atlases or varied intracellular protein localisations, often in multiple experimental conditions. The data mining of those geometrical objects requires a variety of mathematical and computational tools of diverse accessibility and complexity. Here we present a new Python library for quantitative 3D geometry called GeNePy3D which helps handle and mine information and knowledge from geometric data, providing a unified application programming interface (API) to methods from several domains including computational geometry, scale space methods or spatial statistics. By framing this library as generically as possible, and by linking it to as many state-of-the-art reference algorithms and projects as needed, we help render those often specialist methods accessible to a larger community. We exemplify the usefulness of the GeNePy3D toolbox by re-analysing a recently published whole-brain zebrafish neuronal atlas, with other applications and examples available online. Along with an open source, documented and exemplified code, we release reusable containers to allow for convenient and wide usability and increased reproducibility. |
| Databáze: | OpenAIRE |
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