Learning and teaching biological data science in the Bioconductor community

Drnevich, Jenny; Tan, Frederick J.; Almeida-Silva, Fabricio; Castelo Valdueza, Robert; Culhane, Aedín C.; Davis, Sean; Doyle, Maria A.; Geistlinger, Ludwig; Ghazi, Andrew R.; Holmes, Susan; Lahti, Leo; Mahmoud, Alexandru; Nishida, Kozo; Ramos, Marcel; Rue-Albrecht, Kevin; Shih, David J. H.; Gatto, Laurent; Soneson, Charlotte

doi:http://dx.doi.org/10.1371/journal.pcbi.1012925

Learning and teaching biological data science in the Bioconductor community

Citation

Drnevich J, Tan FJ, Almeida-Silva F, Castelo R, Culhane AC, Davis S, et al. Learning and teaching biological data science in the Bioconductor community. PLoS Comput Biol. 2025 Apr 22;21(4):e1012925. DOI: 10.1371/journal.pcbi.1012925

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.