4.7 Article

The digital revolution in phenotyping

期刊

BRIEFINGS IN BIOINFORMATICS
卷 17, 期 5, 页码 819-830

出版社

OXFORD UNIV PRESS
DOI: 10.1093/bib/bbv083

关键词

phenomics; phenotypes; acquisition; interoperability; semantic representation; knowledge discovery

资金

  1. National Institutes of Health [1 U54 HG006370-01, R01 LM011369, R01 GM101430, U54 HG004028, T15 LM00707, R01-LM008111, R01 GM102282, U24 CA143840, U54HG006370, U54 HG008033-01]
  2. Wellcome Trust [098051]
  3. Marie Curie experience researcher fellowship [301806]
  4. National Science Foundation [1207592, DBI-1062404, DBI-1062542, EF-0905606]
  5. Bundesministerium fur Bildung und Forschung [0313911]
  6. European Community's Seventh Framework Programme [602300]
  7. European Community's Seventh Framework Programme [SYBIL]
  8. Systems Microscopy NoE project [258068]
  9. Defense Advanced Research Projects Agency [W911NF-14-C-0109]
  10. Kinghorn Foundation
  11. Intramural Research Program of the NIH, National Library of Medicine
  12. Medical Research Council
  13. Homer Warner Center for Informatics Research of the IHC Health Services
  14. Div Of Biological Infrastructure
  15. Direct For Biological Sciences [1062542] Funding Source: National Science Foundation
  16. Div Of Information & Intelligent Systems
  17. Direct For Computer & Info Scie & Enginr [1207592] Funding Source: National Science Foundation
  18. Medical Research Council [MR/M025160/1] Funding Source: researchfish
  19. MRC [MR/M025160/1, MC_U142684171] Funding Source: UKRI

向作者/读者索取更多资源

Phenotypes have gained increased notoriety in the clinical and biological domain owing to their application in numerous areas such as the discovery of disease genes and drug targets, phylogenetics and pharmacogenomics. Phenotypes, defined as observable characteristics of organisms, can be seen as one of the bridges that lead to a translation of experimental findings into clinical applications and thereby support 'bench to bedside' efforts. However, to build this translational bridge, a common and universal understanding of phenotypes is required that goes beyond domain-specific definitions. To achieve this ambitious goal, a digital revolution is ongoing that enables the encoding of data in computer-readable formats and the data storage in specialized repositories, ready for integration, enabling translational research. While phenome research is an ongoing endeavor, the true potential hidden in the currently available data still needs to be unlocked, offering exciting opportunities for the forthcoming years. Here, we provide insights into the state-of-the-art in digital phenotyping, by means of representing, acquiring and analyzing phenotype data. In addition, we provide visions of this field for future research work that could enable better applications of phenotype data.

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