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.
| Original language | English (US) |
|---|---|
| Journal | PLoS biology |
| Volume | 13 |
| Issue number | 1 |
| DOIs | |
| State | Published - Jan 1 2015 |
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ASJC Scopus subject areas
- Neuroscience(all)
- Biochemistry, Genetics and Molecular Biology(all)
- Immunology and Microbiology(all)
- Agricultural and Biological Sciences(all)
Cite this
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; 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.
In: PLoS biology, Vol. 13, No. 1, 01.01.2015.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Finding Our Way through Phenotypes
AU - Deans, Andrew R.
AU - Lewis, Suzanna E.
AU - Huala, Eva
AU - Anzaldo, Salvatore S.
AU - Ashburner, Michael
AU - Balhoff, James P.
AU - Blackburn, David C.
AU - Blake, Judith A.
AU - Burleigh, J. Gordon
AU - Chanet, Bruno
AU - Cooper, Laurel D.
AU - Courtot, Mélanie
AU - Csösz, Sándor
AU - Cui, Hong
AU - Dahdul, Wasila
AU - Das, Sandip
AU - Dececchi, T. Alexander
AU - Dettai, Agnes
AU - Diogo, Rui
AU - Druzinsky, Robert E.
AU - Dumontier, Michel
AU - Franz, Nico M.
AU - Friedrich, Frank
AU - Gkoutos, George V.
AU - Haendel, Melissa
AU - Harmon, Luke J.
AU - Hayamizu, Terry F.
AU - He, Yongqun
AU - Hines, Heather M.
AU - Ibrahim, Nizar
AU - Jackson, Laura M.
AU - Jaiswal, Pankaj
AU - James-Zorn, Christina
AU - Köhler, Sebastian
AU - Lecointre, Guillaume
AU - Lapp, Hilmar
AU - Lawrence, Carolyn J.
AU - Le Novère, Nicolas
AU - Lundberg, John G.
AU - Macklin, James
AU - Mast, Austin R.
AU - Midford, Peter E.
AU - Mikó, István
AU - Mungall, Christopher J.
AU - Oellrich, Anika
AU - Osumi-Sutherland, David
AU - Parkinson, Helen
AU - Ramírez, Martín J.
AU - Richter, Stefan
AU - Robinson, Peter N.
AU - Ruttenberg, Alan
AU - Schulz, Katja S.
AU - Segerdell, Erik
AU - Seltmann, Katja C.
AU - Sharkey, Michael J.
AU - Smith, Aaron D.
AU - Smith, Barry
AU - Specht, Chelsea D.
AU - Squires, R. Burke
AU - Thacker, Robert W.
AU - Thessen, Anne
AU - Fernandez-Triana, Jose
AU - Vihinen, Mauno
AU - Vize, Peter D.
AU - Vogt, Lars
AU - Wall, Christine E.
AU - Walls, Ramona L.
AU - Westerfeld, Monte
AU - Wharton, Robert A.
AU - Wirkner, Christian S.
AU - Woolley, James B.
AU - Yoder, Matthew J.
AU - Zorn, Aaron M.
AU - Mabee, Paula
PY - 2015/1/1
Y1 - 2015/1/1
N2 - 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.
AB - 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.
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UR - http://www.scopus.com/inward/citedby.url?scp=84922211548&partnerID=8YFLogxK
U2 - 10.1371/journal.pbio.1002033
DO - 10.1371/journal.pbio.1002033
M3 - Article
C2 - 25562316
AN - SCOPUS:84922211548
VL - 13
JO - PLoS Biology
JF - PLoS Biology
SN - 1544-9173
IS - 1
ER -