Learning and teaching biological data science in the Bioconductor community. - 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; et al. (PLoS Computational Biology)
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.