Article
Finding our way through phenotypes.
PLoS biology - 1 Jan 2015
Deans Andrew R, Lewis Suzanna E, Huala Eva, Anzaldo Salvatore S, Ashburner Michael, Balhoff James P, Blackburn David C, Blake Judith A, Burleigh J Gordon, Chanet Bruno, Cooper Laurel D, Courtot Mélanie, Csösz Sándor, Cui Hong, Dahdul Wasila, Das Sandip, Dececchi T Alexander, Dettai Agnes, Diogo Rui, Druzinsky Robert E, Dumontier Michel, Franz Nico M, Friedrich Frank, Gkoutos George V, Haendel Melissa, Harmon Luke J, Hayamizu Terry F, He Yongqun, Hines Heather M, Ibrahim Nizar, Jackson Laura M, Jaiswal Pankaj, James-Zorn Christina, Köhler Sebastian, Lecointre Guillaume, Lapp Hilmar, Lawrence Carolyn J, Le Novère Nicolas, Lundberg John G, Macklin James, Mast Austin R, Midford Peter E, Mikó István, Mungall Christopher J, Oellrich Anika, Osumi-Sutherland David, Parkinson Helen, Ramírez Martín J, Richter Stefan, Robinson Peter N, Ruttenberg Alan, Schulz Katja S, Segerdell Erik, Seltmann Katja C, Sharkey Michael J, Smith Aaron D, Smith Barry, Specht Chelsea D, Squires R Burke, Thacker Robert W, Thessen Anne, Fernandez-Triana Jose, Vihinen Mauno, Vize Peter D, Vogt Lars, Wall Christine E, Walls Ramona L, Westerfeld Monte, Wharton Robert A, Wirkner Christian S, Woolley James B, Yoder Matthew J, Zorn Aaron M, Mabee Paula
Abstract excerpt
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 contexts is perhaps the most pressing scientific bottleneck to integration across many key fields in biology,...
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