Learning and teaching biological data science in the Bioconductor community

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 J. H.; Gatto, Laurent; Soneson, Charlotte
Learning and teaching biological data science in the Bioconductor community

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 J. H.
Gatto, Laurent
Soneson, Charlotte
Katso/Avaa
Lataukset: 

Public Library of Science (PLoS)
doi:10.1371/journal.pcbi.1012925
URI
https://doi.org/10.1371/journal.pcbi.1012925
Näytä kaikki kuvailutiedot
Julkaisun pysyvä osoite on:
https://urn.fi/URN:NBN:fi-fe2025082785744
Tiivistelmä
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.
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