Commentary


Nature Methods 7, S2 - S4 (2010)
doi:10.1038/nmeth.f.301

Visualizing biological data—now and in the future

Seán I O'Donoghue1, Anne-Claude Gavin1, Nils Gehlenborg2,3, David S Goodsell4, Jean-Karim Hériché1, Cydney B Nielsen5, Chris North6, Arthur J Olson4, James B Procter7, David W Shattuck8, Thomas Walter1 & Bang Wong9

  1. European Molecular Biology Laboratory, Heidelberg, Germany.
  2. European Bioinformatics Institute, Cambridge, UK.
  3. Graduate School of Life Sciences, University of Cambridge, Cambridge, UK.
  4. The Scripps Research Institute, La Jolla, California, USA.
  5. British Columbia Cancer Agency, Genome Sciences Centre, Vancouver, British Columbia, Canada.
  6. Virginia Tech, Blacksburg, Virginia, USA.
  7. School of Life Sciences Research, College of Life Sciences, University of Dundee, Dundee, UK.
  8. Laboratory of Neuro Imaging, University of California, Los Angeles, California, USA.
  9. Broad Institute of MIT & Harvard, Cambridge, Massachusetts, USA.

Correspondence to: Seán I O'Donoghue1 e-mail: sean.odonoghue@embl.de.


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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