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Bioconductor: Open software development for computational biology and bioinformatics
Bioconductor Project Working Papers
  • Robert C. Gentleman, Department of Biostatistical Sciences, Dana Farber Cancer Institute
  • Vincent J. Carey, Channing Laboratory, Brigham and Women's Hospital
  • Douglas J. Bates, Department of Statistics, University of Wisconsin, Madison
  • Benjamin M. Bolstad, Division of Biostatistics, University of California, Berkeley
  • Marcel Dettling, Seminar for Statistics, ETH, Zurich, CH
  • Sandrine Dudoit, Division of Biostatistics, University of California, Berkeley
  • Byron Ellis, Department of Statistics, Harvard University
  • Laurent Gautier, Center for Biological Sequence Analysis, Technical University of Denmark, DK
  • Yongchao Ge, Department of Biomathematical Sciences, Mount Sinai School of Medicine
  • Jeff Gentry, Department of Biostatistical Sciences, Dana Farber Cancer Institute
  • Kurt Hornik, Computational Statistics Group, Department of Statistics and Mathematics, Wirtschaftsuniversität Wien, AT
  • Torsten Hothorn, Institut fuer Medizininformatik, Biometrie und Epidemiologie, Friedrich-Alexander-Universitat Erlangen-Nurnberg, DE
  • Wolfgang Huber, Department for Molecular Genome Analysis (B050), German Cancer Research Center, Heidelberg, DE
  • Stefano Iacus, Department of Economics, University of Milan, IT
  • Rafael Irizarry, Department of Biostatistics, Johns Hopkins University
  • Friedrich Leisch, Institut für Statistik und Wahrscheinlichkeitstheorie, Technische Universität Wien, AT
  • Cheng Li, Department of Biostatistical Sciences, Dana Farber Cancer Institute
  • Martin Maechler, Seminar for Statistics, ETH, Zurich, CH
  • Anthony J. Rossini, Department of Medical Education and Biomedical Informatics, University of Washington
  • Guenther Sawitzki, Statistisches Labor, Institut fuer Angewandte Mathematik, DE
  • Colin Smith, Department of Molecular Biology, The Scripps Research Institute, San Diego
  • Gordon K. Smyth, Division of Genetics and Bioinformatics, The Walter and Eliza Hall Institute of Medical Research, Melbourne, AU
  • Luke Tierney, Department of Statistics and Actuarial Science, University of Iowa
  • Yee Hwa Yang, Center for Bioinformatics and Molecular Biostatistics, Univerisity of California, San Francisco
  • Jianhua Zhang, Department of Biostatistical Sciences, Dana Farber Cancer Institute
Date of this Version
1-1-2004
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.

Citation Information
Robert C. Gentleman, Vincent J. Carey, Douglas J. Bates, Benjamin M. Bolstad, et al.. "Bioconductor: Open software development for computational biology and bioinformatics" (2004)
Available at: http://works.bepress.com/anthony_rossini/5/