Author
Andrew Deans
Suzanna Lewis
Eva Huala
Salvatore Anzaldo
Michael Ashburner
James Balhoff
David Blackburn
Judith Blake
Gordon Burleigh
Bruno Chanet
Laurel Cooper
Mélanie Courtot
Sándor Csösz
Hong Cui
Wasila Dahdul
Sandip Das
Alexander Dececchi
Agnes Dettai
Rui Diogo
Robert Druzinsky
Michel Dumontier
Nico Franz
Frank Friedrich
George Gkoutos
Melissa Haendel
Luke Harmon
Terry Hayamizu
Yongqun He
Heather Hines
Nizar Ibrahim
Laura Jackson
Pankaj Jaiswal
Christina James-Zorn
Sebastian Köhler
Guillaume Lecointre
Hilmar Lapp
Carolyn Lawrence
Nicolas Le Novère
John Lundberg
James Macklin
Austin Mast
Peter Midford
István Mikó
Christopher Mungall
Anika Oellrich
David Osumi-Sutherland
Helen Parkinson
Martín Ramírez
Stefan Richter
Peter Robinson
Alan Ruttenberg
Katja Schulz
Erik Segerdell
Katja Seltmann
Michael Sharkey
Aaron Smith
Barry Smith
Chelsea Specht
Burke Squires
Robert Thacker
Anne Thessen
Jose Fernandez-Triana
Mauno Vihinen
Peter Vize
Lars Vogt
Christine Wall
Ramona Walls
Monte Westerfeld
Robert Wharton
Christian Wirkner
James Woolley
Matthew Yoder
Aaron Zorn
Paula Mabee
Abstract

<sec> <title></title> <p>Imagine if we could compute across phenotype data as easily as genomic data; this article calls for efforts to realize this vision and discusses the potential benefits.</p> </sec>
Year of Publication
2015
Journal
PLoS Biol
Volume
13
Number of Pages
e1002033
Date Published
01
URL
http://dx.doi.org/10.1371%2Fjournal.pbio.1002033
DOI
10.1371/journal.pbio.1002033
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