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Bioconductor: software and development strategies for statistical genomics

Part 4. Bioinformatics

4.8. Modern Programming Paradigms in Biology

Specialist Review

  1. Robert Gentleman1,
  2. Vincent Carey2

Published Online: 15 APR 2005

DOI: 10.1002/047001153X.g409207

Encyclopedia of Genetics, Genomics, Proteomics and Bioinformatics

Encyclopedia of Genetics, Genomics, Proteomics and Bioinformatics

How to Cite

Gentleman, R. and Carey, V. 2005. Bioconductor: software and development strategies for statistical genomics. Encyclopedia of Genetics, Genomics, Proteomics and Bioinformatics. 4:4.8:95.

Author Information

  1. 1

    Dana-Farber Cancer Institute, Boston, MA, USA

  2. 2

    Brigham and Women's Hospital, Boston, MA, USA

Publication History

  1. Published Online: 15 APR 2005

Abstract

Bioconductor is an open source initiative for the creation and dissemination of methods in statistical genomics and computational biology based on R. This article describes the requirements, language features, and methodology of design and development guiding the evolution of this project. Commitments to software interoperability, computable task-oriented documentation, and full transparency of algorithm development and use are found to be valuable in reducing barriers to access faced by statistical, computational, or biological researchers attempting interdisciplinary work. These commitments are expected to foster the propagation of standards of transparency and explicit reproducibility from wet-lab science, where they are well accepted, to in silico biology, where explicit reproduction of important published results is often very difficult.

Keywords:

  • computational biology;
  • open source software;
  • object-oriented programming;
  • documentation;
  • network algorithms;
  • software quality assurance;
  • reproducible research