Authors

Robert C. Gentleman, Department of Biostatistical Sciences, Dana Farber Cancer InstituteFollow
Vincent J. Carey, Channing Laboratory, Brigham and Women's HospitalFollow
Douglas J. Bates, Department of Statistics, University of Wisconsin, MadisonFollow
Benjamin M. Bolstad, Division of Biostatistics, University of California, BerkeleyFollow
Marcel Dettling, Seminar for Statistics, ETH, Zurich, CHFollow
Sandrine Dudoit, Division of Biostatistics, University of California, BerkeleyFollow
Byron Ellis, Department of Statistics, Harvard UniversityFollow
Laurent Gautier, Center for Biological Sequence Analysis, Technical University of Denmark, DKFollow
Yongchao Ge, Department of Biomathematical Sciences, Mount Sinai School of MedicineFollow
Jeff Gentry, Department of Biostatistical Sciences, Dana Farber Cancer InstituteFollow
Kurt Hornik, Computational Statistics Group, Department of Statistics and Mathematics, Wirtschaftsuniversität Wien, ATFollow
Torsten Hothorn, Institut fuer Medizininformatik, Biometrie und Epidemiologie, Friedrich-Alexander-Universitat Erlangen-Nurnberg, DEFollow
Wolfgang Huber, Department for Molecular Genome Analysis (B050), German Cancer Research Center, Heidelberg, DEFollow
Stefano Iacus, Department of Economics, University of Milan, ITFollow
Rafael Irizarry, Department of Biostatistics, Johns Hopkins UniversityFollow
Friedrich Leisch, Institut für Statistik und Wahrscheinlichkeitstheorie, Technische Universität Wien, ATFollow
Cheng Li, Department of Biostatistical Sciences, Dana Farber Cancer InstituteFollow
Martin Maechler, Seminar for Statistics, ETH, Zurich, CHFollow
Anthony J. Rossini, Department of Medical Education and Biomedical Informatics, University of WashingtonFollow
Guenther Sawitzki, Statistisches Labor, Institut fuer Angewandte Mathematik, DEFollow
Colin Smith, Department of Molecular Biology, The Scripps Research Institute, San DiegoFollow
Gordon K. Smyth, Division of Genetics and Bioinformatics, The Walter and Eliza Hall Institute of Medical Research, Melbourne, AUFollow
Luke Tierney, Department of Statistics and Actuarial Science, University of IowaFollow
Yee Hwa Yang, Center for Bioinformatics and Molecular Biostatistics, Univerisity of California, San FranciscoFollow
Jianhua Zhang, Department of Biostatistical Sciences, Dana Farber Cancer InstituteFollow

Abstract

The Bioconductor project is an initiative for the collaborative creation of extensible software for computational biology and bioinformatics. We detail some of the design decisions, software paradigms and operational strategies that have allowed a small number of researchers to provide a wide variety of innovative, extensible, software solutions in a relatively short time. The use of an object oriented programming paradigm, the adoption and development of a software package system, designing by contract, distributed development and collaboration with other projects are elements of this project's success. Individually, each of these concepts are useful and important but when combined they have provided a strong basis for rapid development and deployment of innovative and flexible research software for scientific computation. A primary objective of this initiative is achievement of total remote reproducibility of novel algorithmic research results.

Disciplines

Bioinformatics | Computational Biology | Numerical Analysis and Computation

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