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
  • , Kozo Nishida
  • , Marcel Ramos
  • , Kevin Rue-Albrecht
  • , David J.H. Shih
  • , Laurent Gatto
  • , Charlotte Soneson

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Article numbere1012925
JournalPLoS Computational Biology
Volume21
Issue number4 APRIL
DOIs
Publication statusPublished - Apr 2025

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