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A Comprehensive, FAIR File Format for Neuroanatomical Structure Modeling
With advances in microscopy and computer science, the technique of digitally reconstructing, modeling, and quantifying microscopic anatomies has become central to many fields of biological research. MBF Bioscience has chosen to openly document their digital reconstruction file format, the Neuromorph...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8975944/ https://www.ncbi.nlm.nih.gov/pubmed/34601704 http://dx.doi.org/10.1007/s12021-021-09530-x |
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author | Sullivan, A. E. Tappan, S. J. Angstman, P. J. Rodriguez, A. Thomas, G. C. Hoppes, D. M. Abdul-Karim, M. A. Heal, M. L. Glaser, Jack R. |
author_facet | Sullivan, A. E. Tappan, S. J. Angstman, P. J. Rodriguez, A. Thomas, G. C. Hoppes, D. M. Abdul-Karim, M. A. Heal, M. L. Glaser, Jack R. |
author_sort | Sullivan, A. E. |
collection | PubMed |
description | With advances in microscopy and computer science, the technique of digitally reconstructing, modeling, and quantifying microscopic anatomies has become central to many fields of biological research. MBF Bioscience has chosen to openly document their digital reconstruction file format, the Neuromorphological File Specification, available at www.mbfbioscience.com/filespecification (Angstman et al., 2020). The format, created and maintained by MBF Bioscience, is broadly utilized by the neuroscience community. The data format’s structure and capabilities have evolved since its inception, with modifications made to keep pace with advancements in microscopy and the scientific questions raised by worldwide experts in the field. More recent modifications to the neuromorphological file format ensure it abides by the Findable, Accessible, Interoperable, and Reusable (FAIR) data principles promoted by the International Neuroinformatics Coordinating Facility (INCF; Wilkinson et al., Scientific Data, 3, 160018,, 2016). The incorporated metadata make it easy to identify and repurpose these data types for downstream applications and investigation. This publication describes key elements of the file format and details their relevant structural advantages in an effort to encourage the reuse of these rich data files for alternative analysis or reproduction of derived conclusions. |
format | Online Article Text |
id | pubmed-8975944 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-89759442022-10-08 A Comprehensive, FAIR File Format for Neuroanatomical Structure Modeling Sullivan, A. E. Tappan, S. J. Angstman, P. J. Rodriguez, A. Thomas, G. C. Hoppes, D. M. Abdul-Karim, M. A. Heal, M. L. Glaser, Jack R. Neuroinformatics Original Article With advances in microscopy and computer science, the technique of digitally reconstructing, modeling, and quantifying microscopic anatomies has become central to many fields of biological research. MBF Bioscience has chosen to openly document their digital reconstruction file format, the Neuromorphological File Specification, available at www.mbfbioscience.com/filespecification (Angstman et al., 2020). The format, created and maintained by MBF Bioscience, is broadly utilized by the neuroscience community. The data format’s structure and capabilities have evolved since its inception, with modifications made to keep pace with advancements in microscopy and the scientific questions raised by worldwide experts in the field. More recent modifications to the neuromorphological file format ensure it abides by the Findable, Accessible, Interoperable, and Reusable (FAIR) data principles promoted by the International Neuroinformatics Coordinating Facility (INCF; Wilkinson et al., Scientific Data, 3, 160018,, 2016). The incorporated metadata make it easy to identify and repurpose these data types for downstream applications and investigation. This publication describes key elements of the file format and details their relevant structural advantages in an effort to encourage the reuse of these rich data files for alternative analysis or reproduction of derived conclusions. Springer US 2021-10-02 2022 /pmc/articles/PMC8975944/ /pubmed/34601704 http://dx.doi.org/10.1007/s12021-021-09530-x Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Original Article Sullivan, A. E. Tappan, S. J. Angstman, P. J. Rodriguez, A. Thomas, G. C. Hoppes, D. M. Abdul-Karim, M. A. Heal, M. L. Glaser, Jack R. A Comprehensive, FAIR File Format for Neuroanatomical Structure Modeling |
title | A Comprehensive, FAIR File Format for Neuroanatomical Structure Modeling |
title_full | A Comprehensive, FAIR File Format for Neuroanatomical Structure Modeling |
title_fullStr | A Comprehensive, FAIR File Format for Neuroanatomical Structure Modeling |
title_full_unstemmed | A Comprehensive, FAIR File Format for Neuroanatomical Structure Modeling |
title_short | A Comprehensive, FAIR File Format for Neuroanatomical Structure Modeling |
title_sort | comprehensive, fair file format for neuroanatomical structure modeling |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8975944/ https://www.ncbi.nlm.nih.gov/pubmed/34601704 http://dx.doi.org/10.1007/s12021-021-09530-x |
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