Learning and teaching biological data science in the Bioconductor community.
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...
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| Main Authors: | , , , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2025-04-01
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| Series: | PLoS Computational Biology |
| Online Access: | https://doi.org/10.1371/journal.pcbi.1012925 |
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| _version_ | 1849310471111311360 |
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| author | Jenny Drnevich Frederick J Tan Fabricio Almeida-Silva Robert Castelo Aedin C Culhane Sean Davis Maria A Doyle Ludwig Geistlinger Andrew R Ghazi Susan Holmes Leo Lahti Alexandru Mahmoud Kozo Nishida Marcel Ramos Kevin Rue-Albrecht David J H Shih Laurent Gatto Charlotte Soneson |
| author_facet | Jenny Drnevich Frederick J Tan Fabricio Almeida-Silva Robert Castelo Aedin C Culhane Sean Davis Maria A Doyle Ludwig Geistlinger Andrew R Ghazi Susan Holmes Leo Lahti Alexandru Mahmoud Kozo Nishida Marcel Ramos Kevin Rue-Albrecht David J H Shih Laurent Gatto Charlotte Soneson |
| author_sort | Jenny Drnevich |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-ef1673d8988b462996f30fcffa1e788d |
| institution | Kabale University |
| issn | 1553-734X 1553-7358 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Computational Biology |
| spelling | doaj-art-ef1673d8988b462996f30fcffa1e788d2025-08-20T03:53:42ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582025-04-01214e101292510.1371/journal.pcbi.1012925Learning and teaching biological data science in the Bioconductor community.Jenny DrnevichFrederick J TanFabricio Almeida-SilvaRobert CasteloAedin C CulhaneSean DavisMaria A DoyleLudwig GeistlingerAndrew R GhaziSusan HolmesLeo LahtiAlexandru MahmoudKozo NishidaMarcel RamosKevin Rue-AlbrechtDavid J H ShihLaurent GattoCharlotte SonesonModern 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.https://doi.org/10.1371/journal.pcbi.1012925 |
| spellingShingle | Jenny Drnevich Frederick J Tan Fabricio Almeida-Silva Robert Castelo Aedin C Culhane Sean Davis Maria A Doyle Ludwig Geistlinger Andrew R Ghazi Susan Holmes Leo Lahti Alexandru Mahmoud Kozo Nishida Marcel Ramos Kevin Rue-Albrecht David J H Shih Laurent Gatto Charlotte Soneson Learning and teaching biological data science in the Bioconductor community. PLoS Computational Biology |
| title | Learning and teaching biological data science in the Bioconductor community. |
| title_full | Learning and teaching biological data science in the Bioconductor community. |
| title_fullStr | Learning and teaching biological data science in the Bioconductor community. |
| title_full_unstemmed | Learning and teaching biological data science in the Bioconductor community. |
| title_short | Learning and teaching biological data science in the Bioconductor community. |
| title_sort | learning and teaching biological data science in the bioconductor community |
| url | https://doi.org/10.1371/journal.pcbi.1012925 |
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