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Journal article

Learning and teaching biological data science in the Bioconductor community

Abstract:
Modern biological research is increasingly data-intensive, leading to a growing demand for effective training in biological data science. In this article, we provide an overview of key resources and best practices available within the Bioconductor project—an open-source software community focused on omics data analysis. This guide serves as a valuable reference for both learners and educators in the field.
Publication status:
Published
Peer review status:
Peer reviewed

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Role:
Author
ORCID:
0000-0002-1401-8311
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Role:
Author
ORCID:
0000-0003-2229-4508


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Funder identifier:
https://ror.org/05k73zm37


Publisher:
Public Library of Science
Journal:
PLoS Computational Biology More from this journal
Volume:
21
Issue:
4
Article number:
e1012925
Publication date:
2025-04-22
DOI:
EISSN:
1553-7358
ISSN:
1553-734X


Language:
English
Source identifiers:
2880178
Deposit date:
2025-04-22
This ORA record was generated from metadata provided by an external service. It has not been edited by the ORA Team.

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