期刊
PLOS BIOLOGY
卷 13, 期 1, 页码 -出版社
PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pbio.1002033
关键词
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资金
- US National Science Foundation [DEB-0956049]
- Biotechnology and Biological Sciences Research Council [BBS/E/B/000C0419, BBS/E/W/10961A01] Funding Source: researchfish
- Direct For Biological Sciences
- Division Of Environmental Biology [1523605, 1208310, 1208912] Funding Source: National Science Foundation
- Division Of Environmental Biology
- Direct For Biological Sciences [1257601, 1208666, 1155984] Funding Source: National Science Foundation
- Division Of Integrative Organismal Systems
- Direct For Biological Sciences [1127112, 1340112] Funding Source: National Science Foundation
- Div Of Biological Infrastructure
- Direct For Biological Sciences [1062542, 1062404] Funding Source: National Science Foundation
- Div Of Biological Infrastructure
- Direct For Biological Sciences [1147266, 1115210, 0956049, 1062350] Funding Source: National Science Foundation
- BBSRC [BBS/E/W/10961A01, BBS/E/B/000C0419] Funding Source: UKRI
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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