Finding our way through phenotypes.

Finding our way through phenotypes.

Despite a large and multifaceted effort to understand the vast landscape of phenotypic data, their current form inhibits productive data analysis. The lack of a community-wide, consensus-based, human- and machine-interpretable language for describing phenotypes and their genomic and environmental co...

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Bibliographic Details
Main Authors: Andrew R Deans, Suzanna E Lewis, Eva Huala, Salvatore S Anzaldo, Michael Ashburner, James P Balhoff, David C Blackburn, Judith A Blake, J Gordon Burleigh, Bruno Chanet, Laurel D Cooper, Mélanie Courtot, Sándor Csösz, Hong Cui, Wasila Dahdul, Sandip Das, T Alexander Dececchi, Agnes Dettai, Rui Diogo, Robert E Druzinsky, Michel Dumontier, Nico M Franz, Frank Friedrich, George V Gkoutos, Melissa Haendel, Luke J Harmon, Terry F Hayamizu, Yongqun He, Heather M Hines, Nizar Ibrahim, Laura M Jackson, Pankaj Jaiswal, Christina James-Zorn, Sebastian Köhler, Guillaume Lecointre, Hilmar Lapp, Carolyn J Lawrence, Nicolas Le Novère, John G Lundberg, James Macklin, Austin R Mast, Peter E Midford, István Mikó, Christopher J Mungall, Anika Oellrich, David Osumi-Sutherland, Helen Parkinson, Martín J Ramírez, Stefan Richter, Peter N Robinson, Alan Ruttenberg, Katja S Schulz, Erik Segerdell, Katja C Seltmann, Michael J Sharkey, Aaron D Smith, Barry Smith, Chelsea D Specht, R Burke Squires, Robert W Thacker, Anne Thessen, Jose Fernandez-Triana, Mauno Vihinen, Peter D Vize, Lars Vogt, Christine E Wall, Ramona L Walls, Monte Westerfeld, Robert A Wharton, Christian S Wirkner, James B Woolley, Matthew J Yoder, Aaron M Zorn, Paula Mabee
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2015-01-01
Series:PLoS Biology
Online Access:https://doi.org/10.1371/journal.pbio.1002033

Internet

https://doi.org/10.1371/journal.pbio.1002033

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