Neidio i’r brif dudalen lywio Neidio i chwilio Neidio i’r prif gynnwys

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
  • Pennsylvania State University
  • Lawrence Berkeley National Laboratory
  • Phoenix Bioinformatics
  • Arizona State University
  • University of Cambridge
  • National Evolutionary Synthesis Center
  • California Academy of Sciences
  • Jackson Laboratory
  • University of Florida
  • Field Museum of Natural History
  • Oregon State University
  • Simon Fraser University
  • University of Arizona
  • University of South Dakota
  • University of Delhi
  • Howard University
  • University of Illinois Urbana-Champaign
  • Biomedical Informatics Research Center Antwerp
  • Universität Hamburg
  • Oregon Health & Science University
  • University of Idaho
  • University of Michigan Medical School
  • University of Chicago
  • Shriners Hospitals for Children - Cincinnati
  • Charité - Universitätsmedizin Berlin
  • Iowa State University
  • Babraham Institute
  • Russian Academy of Natural Sciences
  • Ottawa Research and Development Centre
  • Florida State University
  • Wellcome Sanger Institute
  • Museu de Ciències Naturals de Barcelona
  • University of Rostock
  • University at Buffalo, State University of New York
  • National Museum of Natural History
  • American Museum of Natural History
  • University of Kentucky
  • Northern Arizona University
  • University of California, Berkeley
  • National Institute of Allergy and Infectious Diseases
  • University of Alabama at Birmingham
  • The Data Detektiv
  • Australian National Insect Collection
  • Lund University
  • University of Calgary
  • Max Planck Institute for Evolutionary Biology
  • Duke University
  • University of Oregon
  • Texas A&M University

Allbwn ymchwil: Cyfraniad at gyfnodolynErthygladolygiad gan gymheiriaid

175 Dyfyniadau (Scopus)
175 Wedi eu Llwytho i Lawr (Pure)

Crynodeb

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.
Iaith wreiddiolSaesneg
Rhif yr erthygle1002033
Nifer y tudalennau9
CyfnodolynPLoS Biology
Cyfrol13
Rhif cyhoeddi1
Dynodwyr Gwrthrych Digidol (DOIs)
StatwsCyhoeddwyd - 06 Ion 2015

NDC y CU

Mae’r allbwn hwn yn cyfrannu at y Nod(au) Datblygu Cynaliadwy canlynol

  1. NDC 3 - Iechyd a Llesiant Da
    NDC 3 Iechyd a Llesiant Da

Ôl bys

Gweld gwybodaeth am bynciau ymchwil 'Finding Our Way through Phenotypes'. Gyda’i gilydd, maen nhw’n ffurfio ôl bys unigryw.

Dyfynnu hyn