The digital revolution in phenotyping Journal Article


Authors: Oellrich, A.; Collier, N.; Groza, T.; Rebholz-Schuhmann, D.; Shah, N.; Bodenreider, O.; Boland, M. R.; Georgiev, I.; Liu, H.; Livingston, K.; Luna, A.; Mallon, A. M.; Manda, P.; Robinson, P. N.; Rustici, G.; Simon, M.; Wang, L.; Winnenburg, R.; Dumontier, M.
Article Title: The digital revolution in phenotyping
Abstract: 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, definei 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, bymea 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. © The Author 2015. Published by Oxford University Press.
Keywords: acquisition; phenotypes; interoperability; knowledge discovery; phenomics; semantic representation
Journal Title: Briefings in Bioinformatics
Volume: 17
Issue: 5
ISSN: 1467-5463
Publisher: Oxford University Press  
Date Published: 2016-09-01
Start Page: 819
End Page: 830
Language: English
DOI: 10.1093/bib/bbv083
PROVIDER: scopus
PMCID: PMC5036847
PUBMED: 26420780
DOI/URL:
Notes: Article -- Export Date: 6 December 2016 -- Source: Scopus
Altmetric
Citation Impact
BMJ Impact Analytics
MSK Authors
  1. Augustin Luna
    9 Luna