Opportunities and Challenges in Democratizing Immunology Datasets

The field of immunology is rapidly progressing toward a systems-level understanding of immunity to tackle complex infectious diseases, autoimmune conditions, cancer, and beyond. In the last couple of decades, advancements in data acquisition techniques have presented opportunities to explore untappe...

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Main Authors: Sanchita Bhattacharya, Zicheng Hu, Atul J. Butte
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-04-01
Series:Frontiers in Immunology
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fimmu.2021.647536/full
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spelling doaj-41d598425ecd42069225303e7c0478d42021-05-06T14:37:44ZengFrontiers Media S.A.Frontiers in Immunology1664-32242021-04-011210.3389/fimmu.2021.647536647536Opportunities and Challenges in Democratizing Immunology DatasetsSanchita Bhattacharya0Sanchita Bhattacharya1Zicheng Hu2Zicheng Hu3Atul J. Butte4Atul J. Butte5Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, United StatesDepartment of Pediatrics, University of California, San Francisco, San Francisco, CA, United StatesBakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, United StatesDepartment of Pediatrics, University of California, San Francisco, San Francisco, CA, United StatesBakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, United StatesDepartment of Pediatrics, University of California, San Francisco, San Francisco, CA, United StatesThe field of immunology is rapidly progressing toward a systems-level understanding of immunity to tackle complex infectious diseases, autoimmune conditions, cancer, and beyond. In the last couple of decades, advancements in data acquisition techniques have presented opportunities to explore untapped areas of immunological research. Broad initiatives are launched to disseminate the datasets siloed in the global, federated, or private repositories, facilitating interoperability across various research domains. Concurrently, the application of computational methods, such as network analysis, meta-analysis, and machine learning have propelled the field forward by providing insight into salient features that influence the immunological response, which was otherwise left unexplored. Here, we review the opportunities and challenges in democratizing datasets, repositories, and community-wide knowledge sharing tools. We present use cases for repurposing open-access immunology datasets with advanced machine learning applications and more.https://www.frontiersin.org/articles/10.3389/fimmu.2021.647536/fullimmunologyopen-accessdemocratizationdata reusepublic repositories
collection DOAJ
language English
format Article
sources DOAJ
author Sanchita Bhattacharya
Sanchita Bhattacharya
Zicheng Hu
Zicheng Hu
Atul J. Butte
Atul J. Butte
spellingShingle Sanchita Bhattacharya
Sanchita Bhattacharya
Zicheng Hu
Zicheng Hu
Atul J. Butte
Atul J. Butte
Opportunities and Challenges in Democratizing Immunology Datasets
Frontiers in Immunology
immunology
open-access
democratization
data reuse
public repositories
author_facet Sanchita Bhattacharya
Sanchita Bhattacharya
Zicheng Hu
Zicheng Hu
Atul J. Butte
Atul J. Butte
author_sort Sanchita Bhattacharya
title Opportunities and Challenges in Democratizing Immunology Datasets
title_short Opportunities and Challenges in Democratizing Immunology Datasets
title_full Opportunities and Challenges in Democratizing Immunology Datasets
title_fullStr Opportunities and Challenges in Democratizing Immunology Datasets
title_full_unstemmed Opportunities and Challenges in Democratizing Immunology Datasets
title_sort opportunities and challenges in democratizing immunology datasets
publisher Frontiers Media S.A.
series Frontiers in Immunology
issn 1664-3224
publishDate 2021-04-01
description The field of immunology is rapidly progressing toward a systems-level understanding of immunity to tackle complex infectious diseases, autoimmune conditions, cancer, and beyond. In the last couple of decades, advancements in data acquisition techniques have presented opportunities to explore untapped areas of immunological research. Broad initiatives are launched to disseminate the datasets siloed in the global, federated, or private repositories, facilitating interoperability across various research domains. Concurrently, the application of computational methods, such as network analysis, meta-analysis, and machine learning have propelled the field forward by providing insight into salient features that influence the immunological response, which was otherwise left unexplored. Here, we review the opportunities and challenges in democratizing datasets, repositories, and community-wide knowledge sharing tools. We present use cases for repurposing open-access immunology datasets with advanced machine learning applications and more.
topic immunology
open-access
democratization
data reuse
public repositories
url https://www.frontiersin.org/articles/10.3389/fimmu.2021.647536/full
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