Learning and teaching biological data science in the Bioconductor community
<|reference_start|>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 omics data analysis. This guide serves as a valuable reference for both learners and educators in the field.<|reference_end|>
@article{drnevich2024learning,
    title={Learning and teaching biological data science in the Bioconductor
  community},
    author={Jenny Drnevich, Frederick J. Tan, Fabricio Almeida-Silva, Robert
  Castelo, Aedin C. Culhane, Sean Davis, Maria A. Doyle, Susan Holmes, Leo
  Lahti, Alexandru Mahmoud, Kozo Nishida, Marcel Ramos, Kevin Rue-Albrecht,
  David J.H. Shih, Laurent Gatto and Charlotte Soneson},
    journal={arXiv preprint arXiv:2410.01351},
    year={2024},
    archivePrefix={arXiv},
    eprint={2410.01351},
    primaryClass={cs.CY q-bio.OT stat.AP}
}