Bioconductor: Open Software Development for Computational Biology and Bioinformatics

Kurt Hornik; Robert Gentleman; Vincent J. Carey; Douglas M. Bates; Ben Bolstad; Marcel Dettling; Sandrine Dudoit; Byron Ellis; Laurent Gautier; Yongchao Ge; Jeff Gentry; Torsten Hothorn; Wolfgang Huber; Stefano M. Iacus; Rafael A. Irizarry; Friedrich Leisch; Cheng Li; Martin Maechler; Anthony Rossini; Günther Sawitzki; Colin A. Smith; Gordon K. Smyth; Luke Tierney; Jean Yang; Jianhua Zhang

Bioconductor: Open Software Development for Computational Biology and Bioinformatics

Kurt Hornik(Vienna University of Economics and Business), Robert Gentleman(Dana-Farber/Harvard Cancer Center), Vincent J. Carey(Brigham and Women's Hospital), Douglas M. Bates(University of Wisconsin–Madison), Ben Bolstad(University of California, Berkeley), Marcel Dettling(ETH Zurich), Sandrine Dudoit, Byron Ellis(Harvard University), Laurent Gautier(Technical University of Denmark), Yongchao Ge(PhytoCeutica (United States)), Jeff Gentry(Dana-Farber/Harvard Cancer Center), Torsten Hothorn(Friedrich-Alexander-Universität Erlangen-Nürnberg), Wolfgang Huber(German Cancer Research Center), Stefano M. Iacus(University of Milan), Rafael A. Irizarry(Johns Hopkins University), Friedrich Leisch(TU Wien), Cheng Li(Dana-Farber Cancer Institute), Martin Maechler(Institut für Angewandte Statistik), Anthony Rossini(University of Washington), Günther Sawitzki(Heidelberg University), Colin A. Smith, Gordon K. Smyth, Luke Tierney(University of Iowa), Jean Yang(The University of Sydney), Jianhua Zhang

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December 26, 2007

Cited by 761

Abstract

The Bioconductor project is an initiative for the collaborative creation of the extensible software for computational biology and bioinformatics. The goals of the project include: fostering collaborative development and widespread use of innovative software, reducing barriers to entry into interdisciplinary scientific research, and promoting the achievement of remote reproducibility of research results. We describe details of our aims and methodes, identify current challenges, compare Bioconductor to other open bioinformatics projects, and provide working examples.

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