Learning and teaching biological data science in the Bioconductor community.

Drnevich J., Tan FJ., Almeida-Silva F., Castelo R., Culhane AC., Davis S., Doyle MA., Geistlinger L., Ghazi AR., Holmes S., Lahti L., Mahmoud A., Nishida K., Ramos M., Rue-Albrecht K., Shih DJH., Gatto L., Soneson C.

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.

DOI

10.1371/journal.pcbi.1012925

Type

Journal article

Journal

PLoS Comput Biol

Publication Date

04/2025

Volume

21

Keywords

Software, Computational Biology, Data Science, Humans, Teaching

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