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Finding Our Way through Phenotypes.

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 and Chanet, Bruno, et al. (2015) In PLoS Biology 13(1).
Abstract
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, including genomics, systems biology, development, medicine, evolution, ecology, and systematics. Here we survey the current phenomics landscape, including data resources and handling, and the progress that has been made to accurately capture relevant data descriptions for phenotypes. We present an example of the kind of integration across... (More)
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, including genomics, systems biology, development, medicine, evolution, ecology, and systematics. Here we survey the current phenomics landscape, including data resources and handling, and the progress that has been made to accurately capture relevant data descriptions for phenotypes. We present an example of the kind of integration across domains that computable phenotypes would enable, and we call upon the broader biology community, publishers, and relevant funding agencies to support efforts to surmount today's data barriers and facilitate analytical reproducibility. (Less)
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PLoS Biology
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13
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1
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Public Library of Science
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  • pmid:25562316
  • wos:000349169900001
  • scopus:84922211548
ISSN
1544-9173
DOI
10.1371/journal.pbio.1002033
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English
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3d7d4c1b-c584-4fec-ac82-8a85b026d0aa (old id 5041059)
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http://www.ncbi.nlm.nih.gov/pubmed/25562316?dopt=Abstract
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2015-02-02 17:58:14
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2017-11-12 03:35:31
@article{3d7d4c1b-c584-4fec-ac82-8a85b026d0aa,
  abstract     = {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, including genomics, systems biology, development, medicine, evolution, ecology, and systematics. Here we survey the current phenomics landscape, including data resources and handling, and the progress that has been made to accurately capture relevant data descriptions for phenotypes. We present an example of the kind of integration across domains that computable phenotypes would enable, and we call upon the broader biology community, publishers, and relevant funding agencies to support efforts to surmount today's data barriers and facilitate analytical reproducibility.},
  articleno    = {e1002033},
  author       = {Deans, Andrew R and Lewis, Suzanna E and Huala, Eva and Anzaldo, Salvatore S and Ashburner, Michael and Balhoff, James P and Blackburn, David C and Blake, Judith A and Burleigh, J Gordon and Chanet, Bruno and Cooper, Laurel D and Courtot, Mélanie and Csösz, Sándor and Cui, Hong and Dahdul, Wasila and Das, Sandip and Dececchi, T Alexander and Dettai, Agnes and Diogo, Rui and Druzinsky, Robert E and Dumontier, Michel and Franz, Nico M and Friedrich, Frank and Gkoutos, George V and Haendel, Melissa and Harmon, Luke J and Hayamizu, Terry F and He, Yongqun and Hines, Heather M and Ibrahim, Nizar and Jackson, Laura M and Jaiswal, Pankaj and James-Zorn, Christina and Köhler, Sebastian and Lecointre, Guillaume and Lapp, Hilmar and Lawrence, Carolyn J and Le Novère, Nicolas and Lundberg, John G and Macklin, James and Mast, Austin R and Midford, Peter E and Mikó, István and Mungall, Christopher J and Oellrich, Anika and Osumi-Sutherland, David and Parkinson, Helen and Ramírez, Martín J and Richter, Stefan and Robinson, Peter N and Ruttenberg, Alan and Schulz, Katja S and Segerdell, Erik and Seltmann, Katja C and Sharkey, Michael J and Smith, Aaron D and Smith, Barry and Specht, Chelsea D and Squires, R Burke and Thacker, Robert W and Thessen, Anne and Fernandez-Triana, Jose and Vihinen, Mauno and Vize, Peter D and Vogt, Lars and Wall, Christine E and Walls, Ramona L and Westerfeld, Monte and Wharton, Robert A and Wirkner, Christian S and Woolley, James B and Yoder, Matthew J and Zorn, Aaron M and Mabee, Paula},
  issn         = {1544-9173},
  language     = {eng},
  number       = {1},
  publisher    = {Public Library of Science},
  series       = {PLoS Biology},
  title        = {Finding Our Way through Phenotypes.},
  url          = {http://dx.doi.org/10.1371/journal.pbio.1002033},
  volume       = {13},
  year         = {2015},
}