A Comprehensive, FAIR File Format for Neuroanatomical Structure Modeling.

A Comprehensive, FAIR File Format for Neuroanatomical Structure Modeling.
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DOI:
10.1007/s12021-021-09530-x
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发表时间:
2022-01
期刊:
影响因子:
3
通讯作者:
Glaser JR
Glaser JR
中科院分区:
医学4区
文献类型:
--
作者:
Sullivan AE;Tappan SJ;Angstman PJ;Rodriguez A;Thomas GC;Hoppes DM;Abdul-Karim MA;Heal ML;Glaser JR

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随着显微镜和计算机科学的进步,数字重建,建模和量化微观解剖结构的技术已经成为生物学研究的许多领域的核心。MBF Bioscience选择公开记录其数字重建文件格式,即神经形态学文件规范,可在www.mbfbioscience.com/filespecification上获得(Angstman等人,)。由MBF Bioscience创建和维护的格式被神经科学界广泛使用。数据格式的结构和功能自成立以来一直在发展,并进行了修改,以跟上显微镜的进步和该领域的全球专家提出的科学问题。最近对神经形态学文件格式的修改确保其遵守由国际神经信息学协调机构(INCF;威尔金森等人,科学数据,3,160018,,)。合并的元数据使识别和重新利用这些数据类型以用于下游应用程序和调查变得容易。本出版物描述了文件格式的关键要素,并详细介绍了其相关的结构优势,以鼓励重用这些丰富的数据文件,用于替代分析或复制得出的结论。
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.,). 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,,). 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.
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