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Finding Our Way through Phenotypes
Journal article   Open access

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, …
PLoS biology, v 13(1), pp e1002033-e1002033
01 Jan 2015
PMID: 25562316
url
https://doi.org/10.1371/journal.pbio.1002033View
Published, Version of Record (VoR)CC BY V4.0 Open

Abstract

Biochemistry & Molecular Biology Biology Life Sciences & Biomedicine Life Sciences & Biomedicine - Other Topics Science & Technology
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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170 citations in Scopus

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Collaboration types
Domestic collaboration
International collaboration
Web of Science research areas
Biochemistry & Molecular Biology
Biology
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