CellRemorph: A Toolkit for Transforming, Selecting, and Slicing 3D Cell Structures on the Road to Morphologically Detailed Astrocyte Simulations
-
Published:2023-05-03
Issue:3
Volume:21
Page:483-500
-
ISSN:1539-2791
-
Container-title:Neuroinformatics
-
language:en
-
Short-container-title:Neuroinform
Author:
Keto LauraORCID, Manninen TiinaORCID
Abstract
AbstractUnderstanding functions of astrocytes can be greatly enhanced by building and simulating computational models that capture their morphological details. Novel computational tools enable utilization of existing morphological data of astrocytes and building models that have appropriate level of details for specific simulation purposes. In addition to analyzing existing computational tools for constructing, transforming, and assessing astrocyte morphologies, we present here the CellRemorph toolkit implemented as an add-on for Blender, a 3D modeling platform increasingly recognized for its utility for manipulating 3D biological data. To our knowledge, CellRemorph is the first toolkit for transforming astrocyte morphologies from polygonal surface meshes into adjustable surface point clouds and vice versa, precisely selecting nanoprocesses, and slicing morphologies into segments with equal surface areas or volumes. CellRemorph is an open-source toolkit under the GNU General Public License and easily accessible via an intuitive graphical user interface. CellRemorph will be a valuable addition to other Blender add-ons, providing novel functionality that facilitates the creation of realistic astrocyte morphologies for different types of morphologically detailed simulations elucidating the role of astrocytes both in health and disease.
Funder
Academy of Finland Tampere University including Tampere University Hospital, Tampere University of Applied Sciences
Publisher
Springer Science and Business Media LLC
Subject
Information Systems,General Neuroscience,Software
Reference80 articles.
1. Abdellah, M., Foni, A., Zisis, E., Guerrero, N. R., Lapere, S., Coggan, J. S., Keller, D., Markram, H., & Schürmann, F. (2021). Metaball skinning of synthetic astroglial morphologies into realistic mesh models for in silico simulations and visual analytics. Bioinformatics, 37, i426–i433. https://doi.org/10.1093/bioinformatics/btab280 2. Abdellah, M., Guerrero, N. R., Lapere, S., Coggan, J. S., Keller, D., Coste, B., Dagar, S., Courcol, J.-D., Markram, H., & Schürmann, F. (2020). Interactive visualization and analysis of morphological skeletons of brain vasculature networks with VessMorphoVis. Bioinformatics, 36, i534–i541. https://doi.org/10.1093/bioinformatics/btaa461 3. Abdellah, M., Hernando, J., Eilemann, S., Lapere, S., Antille, N., Markram, H., & Schürmann, F. (2018). NeuroMorphoVis: A collaborative framework for analysis and visualization of neuronal morphology skeletons reconstructed from microscopy stacks. Bioinformatics, 34(13), i574–i582. https://doi.org/10.1093/bioinformatics/bty231 4. Aguiar, P., Sousa, M., & Szucs, P. (2013). Versatile morphometric analysis and visualization of the three-dimensional structure of neurons. Neuroinformatics, 11(4), 393–403. https://doi.org/10.1007/s12021-013-9188-z 5. Andrei, R. M., Callieri, M., Zini, M. F., Loni, T., Maraziti, G., Pan, M. C., & Zoppè, M. (2012). Intuitive representation of surface properties of biomolecules using BioBlender. BMC Bioinformatics, 13(S4), S16. https://doi.org/10.1186/1471-2105-13-S4-S16
Cited by
2 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
|
|