Finding Our Way through Phenotypes

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

doi:10.1371/journal.pbio.1002033

Finding Our Way through Phenotypes

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. DruzinskyMichel 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

Illinois Natural History Survey

Research output: Contribution to journal › Article › peer-review

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	https://doi.org/10.1371/journal.pbio.1002033
State	Published - 2015

ASJC Scopus subject areas

Neuroscience(all)
Biochemistry, Genetics and Molecular Biology(all)
Immunology and Microbiology(all)
Agricultural and Biological Sciences(all)

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10.1371/journal.pbio.1002033

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Deans, A. R., Lewis, S. E., Huala, E., Anzaldo, S. S., Ashburner, M., Balhoff, J. P., Blackburn, D. C., Blake, J. A., Burleigh, J. G., Chanet, B., Cooper, L. D., Courtot, M., Csösz, S., Cui, H., Dahdul, W., Das, S., Dececchi, T. A., Dettai, A., Diogo, R., ... Mabee, P. (2015). Finding Our Way through Phenotypes. PLoS biology, 13(1). https://doi.org/10.1371/journal.pbio.1002033

Deans, AR, Lewis, SE, Huala, E, Anzaldo, SS, Ashburner, M, Balhoff, JP, Blackburn, DC, Blake, JA, Burleigh, JG, Chanet, B, Cooper, LD, Courtot, M, Csösz, S, Cui, H, Dahdul, W, Das, S, Dececchi, TA, Dettai, A, Diogo, R, Druzinsky, RE, Dumontier, M, Franz, NM, Friedrich, F, Gkoutos, GV, Haendel, M, Harmon, LJ, Hayamizu, TF, He, Y, Hines, HM, Ibrahim, N, Jackson, LM, Jaiswal, P, James-Zorn, C, Köhler, S, Lecointre, G, Lapp, H, Lawrence, CJ, Le Novère, N, Lundberg, JG, Macklin, J, Mast, AR, Midford, PE, Mikó, I, Mungall, CJ, Oellrich, A, Osumi-Sutherland, D, Parkinson, H, Ramírez, MJ, Richter, S, Robinson, PN, Ruttenberg, A, Schulz, KS, Segerdell, E, Seltmann, KC, Sharkey, MJ, Smith, AD, Smith, B, Specht, CD, Squires, RB, Thacker, RW, Thessen, A, Fernandez-Triana, J, Vihinen, M, Vize, PD, Vogt, L, Wall, CE, Walls, RL, Westerfeld, M, Wharton, RA, Wirkner, CS, Woolley, JB, Yoder, MJ, Zorn, AM & Mabee, P 2015, 'Finding Our Way through Phenotypes', PLoS biology, vol. 13, no. 1. https://doi.org/10.1371/journal.pbio.1002033

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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.",

author = "Deans, {Andrew R.} and Lewis, {Suzanna E.} and Eva Huala and Anzaldo, {Salvatore S.} and Michael Ashburner and Balhoff, {James P.} and Blackburn, {David C.} and Blake, {Judith A.} and Burleigh, {J. Gordon} and Bruno Chanet and Cooper, {Laurel D.} and M{\'e}lanie Courtot and S{\'a}ndor Cs{\"o}sz and Hong Cui and Wasila Dahdul and Sandip Das and Dececchi, {T. Alexander} and Agnes Dettai and Rui Diogo and Druzinsky, {Robert E.} and Michel Dumontier and Franz, {Nico M.} and Frank Friedrich and Gkoutos, {George V.} and Melissa Haendel and Harmon, {Luke J.} and Hayamizu, {Terry F.} and Yongqun He and Hines, {Heather M.} and Nizar Ibrahim and Jackson, {Laura M.} and Pankaj Jaiswal and Christina James-Zorn and Sebastian K{\"o}hler and Guillaume Lecointre and Hilmar Lapp and Lawrence, {Carolyn J.} and {Le Nov{\`e}re}, Nicolas and Lundberg, {John G.} and James Macklin and Mast, {Austin R.} and Midford, {Peter E.} and Istv{\'a}n Mik{\'o} and Mungall, {Christopher J.} and Anika Oellrich and David Osumi-Sutherland and Helen Parkinson and Ram{\'i}rez, {Mart{\'i}n J.} and Stefan Richter and Robinson, {Peter N.} and Alan Ruttenberg and Schulz, {Katja S.} and Erik Segerdell and Seltmann, {Katja C.} and Sharkey, {Michael J.} and Smith, {Aaron D.} and Barry Smith and Specht, {Chelsea D.} and Squires, {R. Burke} and Thacker, {Robert W.} and Anne Thessen and Jose Fernandez-Triana and Mauno Vihinen and Vize, {Peter D.} and Lars Vogt and Wall, {Christine E.} and Walls, {Ramona L.} and Monte Westerfeld and Wharton, {Robert A.} and Wirkner, {Christian S.} and Woolley, {James B.} and Yoder, {Matthew J.} and Zorn, {Aaron M.} and Paula Mabee",

note = "Funding Information: Remarkable advances are being made in measuring environmental data, ranging from fine-scale measurements across the surface of a leaf to variation across a planted field to high-resolution environmental layers at a global scale (e.g., ,). As environmental data rapidly accumulate as a result of these new technologies, now is an opportune moment to ensure the usability and longevity of these data by adopting systematic standards. Towards this end, recent workshops funded by NSF and National Institute of Environmental Health Sciences (NIEHS) brought together diverse sets of experts to aid in developing vocabularies and standards for describing environment. Publisher Copyright: {\textcopyright} 2015 Deans et al.",

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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

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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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Finding Our Way through Phenotypes

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