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一种全面的、FAIR 的神经解剖结构建模文件格式。

A Comprehensive, FAIR File Format for Neuroanatomical Structure Modeling.

机构信息

MBF Bioscience, Williston, VT, USA.

出版信息

Neuroinformatics. 2022 Jan;20(1):221-240. doi: 10.1007/s12021-021-09530-x. Epub 2021 Oct 2.

Abstract

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.

摘要

随着显微镜技术和计算机科学的进步,数字化重建、建模和量化微观解剖结构的技术已成为许多生物学研究领域的核心技术。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 上获取(Angstman 等人,2020 年)。该格式由 MBF Bioscience 创建和维护,被神经科学界广泛使用。自成立以来,该数据格式的结构和功能不断发展,对其进行了修改以跟上显微镜技术的进步以及该领域全球专家提出的科学问题的步伐。最近对神经形态学文件格式的修改确保其符合可发现性、可访问性、互操作性和可重复性(FAIR)数据原则,这些原则由国际神经信息学协调设施(INCF;Wilkinson 等人,Scientific Data,3,160018,2016 年)推广。其中包含的元数据使得很容易识别和重新利用这些数据类型,用于下游应用和调查。本出版物描述了文件格式的关键要素,并详细说明了它们在结构上的相关优势,以鼓励对这些丰富的数据文件进行替代分析或重新生成衍生结论。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ed81/9537205/ee4475434b48/12021_2021_9530_Fig1_HTML.jpg

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