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Visualizing biological data—now and in the future

Nature Methods volume 7, pages S2–S4 (2010)Cite this article

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Methods and tools for visualizing biological data have improved considerably over the last decades, but they are still inadequate for some high-throughput data sets. For most users, a key challenge is to benefit from the deluge of data without being overwhelmed by it. This challenge is still largely unfulfilled and will require the development of truly integrated and highly useable tools.

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Figure 1: Possible integrated visualization environment.

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Author information

Authors and Affiliations

  1. European Molecular Biology Laboratory, Heidelberg, Germany

    Seán I O'Donoghue, Anne-Claude Gavin, Jean-Karim Hériché & Thomas Walter

  2. European Bioinformatics Institute, Cambridge, UK

    Nils Gehlenborg

  3. Graduate School of Life Sciences, University of Cambridge, Cambridge, UK

    Nils Gehlenborg

  4. The Scripps Research Institute, La Jolla, California, USA

    David S Goodsell & Arthur J Olson

  5. British Columbia Cancer Agency, Genome Sciences Centre, Vancouver, British Columbia, Canada

    Cydney B Nielsen

  6. Virginia Tech, Blacksburg, Virginia, USA

    Chris North

  7. School of Life Sciences Research, College of Life Sciences, University of Dundee, Dundee, UK

    James B Procter

  8. Laboratory of Neuro Imaging, University of California, Los Angeles, California, USA

    David W Shattuck

  9. Broad Institute of MIT & Harvard, Cambridge, Massachusetts, USA

    Bang Wong

Authors
  1. Seán I O'Donoghue
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  2. Anne-Claude Gavin
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  3. Nils Gehlenborg
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  4. David S Goodsell
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  5. Jean-Karim Hériché
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  6. Cydney B Nielsen
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  7. Chris North
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  8. Arthur J Olson
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  9. James B Procter
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  10. David W Shattuck
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  11. Thomas Walter
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  12. Bang Wong
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Corresponding author

Correspondence to Seán I O'Donoghue.

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The authors declare no competing financial interests.

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O'Donoghue, S., Gavin, AC., Gehlenborg, N. et al. Visualizing biological data—now and in the future. Nat Methods 7 (Suppl 3), S2–S4 (2010). https://doi.org/10.1038/nmeth.f.301

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