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Pancreatlas: Applying an Adaptable Framework to Map the Human Pancreas in Health and Disease

Human tissue phenotyping generates complex spatial information from numerous imaging modalities, yet images typically become static figures for publication, and original data and metadata are rarely available. While comprehensive image maps exist for some organs, most resources have limited support...

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Detalles Bibliográficos
Autores principales: Saunders, Diane C., Messmer, James, Kusmartseva, Irina, Beery, Maria L., Yang, Mingder, Atkinson, Mark A., Powers, Alvin C., Cartailler, Jean-Philippe, Brissova, Marcela
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7691395/
https://www.ncbi.nlm.nih.gov/pubmed/33294866
http://dx.doi.org/10.1016/j.patter.2020.100120
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author Saunders, Diane C.
Messmer, James
Kusmartseva, Irina
Beery, Maria L.
Yang, Mingder
Atkinson, Mark A.
Powers, Alvin C.
Cartailler, Jean-Philippe
Brissova, Marcela
author_facet Saunders, Diane C.
Messmer, James
Kusmartseva, Irina
Beery, Maria L.
Yang, Mingder
Atkinson, Mark A.
Powers, Alvin C.
Cartailler, Jean-Philippe
Brissova, Marcela
author_sort Saunders, Diane C.
collection PubMed
description Human tissue phenotyping generates complex spatial information from numerous imaging modalities, yet images typically become static figures for publication, and original data and metadata are rarely available. While comprehensive image maps exist for some organs, most resources have limited support for multiplexed imaging or have non-intuitive user interfaces. Therefore, we built a Pancreatlas resource that integrates several technologies into a unique interface, allowing users to access richly annotated web pages, drill down to individual images, and deeply explore data online. The current version of Pancreatlas contains over 800 unique images acquired by whole-slide scanning, confocal microscopy, and imaging mass cytometry, and is available at https://www.pancreatlas.org. To create this human pancreas-specific biological imaging resource, we developed a React-based web application and Python-based application programming interface, collectively called Flexible Framework for Integrating and Navigating Data (FFIND), which can be adapted beyond Pancreatlas to meet countless imaging or other structured data-management needs.
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spelling pubmed-76913952020-12-07 Pancreatlas: Applying an Adaptable Framework to Map the Human Pancreas in Health and Disease Saunders, Diane C. Messmer, James Kusmartseva, Irina Beery, Maria L. Yang, Mingder Atkinson, Mark A. Powers, Alvin C. Cartailler, Jean-Philippe Brissova, Marcela Patterns (N Y) Descriptor Human tissue phenotyping generates complex spatial information from numerous imaging modalities, yet images typically become static figures for publication, and original data and metadata are rarely available. While comprehensive image maps exist for some organs, most resources have limited support for multiplexed imaging or have non-intuitive user interfaces. Therefore, we built a Pancreatlas resource that integrates several technologies into a unique interface, allowing users to access richly annotated web pages, drill down to individual images, and deeply explore data online. The current version of Pancreatlas contains over 800 unique images acquired by whole-slide scanning, confocal microscopy, and imaging mass cytometry, and is available at https://www.pancreatlas.org. To create this human pancreas-specific biological imaging resource, we developed a React-based web application and Python-based application programming interface, collectively called Flexible Framework for Integrating and Navigating Data (FFIND), which can be adapted beyond Pancreatlas to meet countless imaging or other structured data-management needs. Elsevier 2020-10-05 /pmc/articles/PMC7691395/ /pubmed/33294866 http://dx.doi.org/10.1016/j.patter.2020.100120 Text en © 2020 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Descriptor
Saunders, Diane C.
Messmer, James
Kusmartseva, Irina
Beery, Maria L.
Yang, Mingder
Atkinson, Mark A.
Powers, Alvin C.
Cartailler, Jean-Philippe
Brissova, Marcela
Pancreatlas: Applying an Adaptable Framework to Map the Human Pancreas in Health and Disease
title Pancreatlas: Applying an Adaptable Framework to Map the Human Pancreas in Health and Disease
title_full Pancreatlas: Applying an Adaptable Framework to Map the Human Pancreas in Health and Disease
title_fullStr Pancreatlas: Applying an Adaptable Framework to Map the Human Pancreas in Health and Disease
title_full_unstemmed Pancreatlas: Applying an Adaptable Framework to Map the Human Pancreas in Health and Disease
title_short Pancreatlas: Applying an Adaptable Framework to Map the Human Pancreas in Health and Disease
title_sort pancreatlas: applying an adaptable framework to map the human pancreas in health and disease
topic Descriptor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7691395/
https://www.ncbi.nlm.nih.gov/pubmed/33294866
http://dx.doi.org/10.1016/j.patter.2020.100120
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