在生物导体社区中学习与教授生物数据科学。
Learning and teaching biological data science in the Bioconductor community.
作者信息
Drnevich Jenny, Tan Frederick J, Almeida-Silva Fabricio, Castelo Robert, Culhane Aedin 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 Jh, Gatto Laurent, Soneson Charlotte
机构信息
Roy J. Carver Biotechnology Center, University of Illinois Urbana-Champaign, Illinois, USA.
Johns Hopkins University, Department of Biology, Baltimore, Maryland, USA.
出版信息
ArXiv. 2025 Mar 11:arXiv:2410.01351v2.
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.
现代生物学研究的数据密集度越来越高，导致对生物数据科学有效培训的需求不断增长。在本文中，我们概述了Bioconductor项目中可用的关键资源和最佳实践，该项目是一个专注于组学数据分析的开源软件社区。本指南对该领域的学习者和教育工作者都具有宝贵的参考价值。
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