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Connectomics Annotation Metadata Standardization for Increased Accessibility and Queryability.
Sanchez, Morgan; Moore, Dymon; Johnson, Erik C; Wester, Brock; Lichtman, Jeff W; Gray-Roncal, William.
Afiliação
  • Sanchez M; Research and Exploratory Development Department, Johns Hopkins University Applied Physics Laboratory, Laurel, MD, United States.
  • Moore D; Research and Exploratory Development Department, Johns Hopkins University Applied Physics Laboratory, Laurel, MD, United States.
  • Johnson EC; Research and Exploratory Development Department, Johns Hopkins University Applied Physics Laboratory, Laurel, MD, United States.
  • Wester B; Research and Exploratory Development Department, Johns Hopkins University Applied Physics Laboratory, Laurel, MD, United States.
  • Lichtman JW; Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA, United States.
  • Gray-Roncal W; Research and Exploratory Development Department, Johns Hopkins University Applied Physics Laboratory, Laurel, MD, United States.
Front Neuroinform ; 16: 828458, 2022.
Article em En | MEDLINE | ID: mdl-35651719
ABSTRACT
Neuroscientists can leverage technological advances to image neural tissue across a range of different scales, potentially forming the basis for the next generation of brain atlases and circuit reconstructions at submicron resolution, using Electron Microscopy and X-ray Microtomography modalities. However, there is variability in data collection, annotation, and storage approaches, which limits effective comparative and secondary analysis. There has been great progress in standardizing interfaces for large-scale spatial image data, but more work is needed to standardize annotations, especially metadata associated with neuroanatomical entities. Standardization will enable validation, sharing, and replication, greatly amplifying investment throughout the connectomics community. We share key design considerations and a usecase developed for metadata for a recent large-scale dataset.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Front Neuroinform Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Front Neuroinform Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Estados Unidos
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