Finding Our Way through Phenotypes

PLoS Biol 13 (1):e1002033 (2015)
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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.
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First archival date: 2016-07-03
Latest version: 2 (2017-11-06)
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References found in this work BETA
The OBO Foundry: Coordinated Evolution of Ontologies to Support Biomedical Data Integration.Smith, Barry; Ashburner, Michael; Rosse, Cornelius; Bard, Jonathan; Bug, William; Ceusters, Werner; Goldberg, Louis J.; Eilbeck, Karen; Ireland, Amelia; Mungall, Christopher J.; Leontis, Neocles & Others,
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The “Street Light Syndrome”, or How Protein Taxonomy Can Bias Experimental Manipulations.Markov, Gabriel; Lecointre, Guillaume; Demeneix, Barbara & Laudet, Vincent

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2015-01-07

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