TY - JOUR
T1 - The digital revolution in phenotyping
AU - Oellrich, Anika
AU - Collier, Nigel
AU - Groza, Tudor
AU - Rebholz-Schuhmann, Dietrich
AU - Shah, Nigam
AU - Bodenreider, Olivier
AU - Boland, Mary Regina
AU - Georgiev, Ivo
AU - Liu, Hongfang
AU - Livingston, Kevin
AU - Luna, Augustin
AU - Mallon, Ann Marie
AU - Manda, Prashanti
AU - Robinson, Peter N.
AU - Rustici, Gabriella
AU - Simon, Michelle
AU - Wang, Liqin
AU - Winnenburg, Rainer
AU - Dumontier, Michel
N1 - Funding Information:
This work was supported by the National Institutes of Health [1 U54 HG006370-01 to A.O., R01 LM011369 and R01 GM101430 and U54 HG004028 to N.H.S., T15 LM00707 to M.R.B., R01-LM008111 to K.L., R01 GM102282 and R01 LM011369 to H.L., U24 CA143840 to A.L., U54HG006370 to A.M., U54 HG008033-01 to M.D.]; the Wellcome Trust [098051 to A.O.]; a Marie Curie experience researcher fellowship [301806 to N.C.]; the National Science Foundation [1207592 to I.G., DBI-1062404 and DBI-1062542 and EF-0905606 to P.M.]; the Bundesministerium für Bildung und Forschung [0313911 to P.N.R.]; the European Community's Seventh Framework Programme [Grant Agreement 602300; SYBIL to P.N.R]; the Systems Microscopy NoE project [grant agreement 258068 to G.R.]; and the Defense Advanced Research Projects Agency [W911NF-14-C-0109 to K.L.]. T.G. was supported by the Kinghorn Foundation. O.B. was supported by the Intramural Research Program of the NIH, National Library of Medicine. M.S. was supported by the Medical Research Council. L.W. was supported by the Homer Warner Center for Informatics Research of the IHC Health Services. R.W. was supported by an appointment to the NLM Research Participation Program administered by the Oak Ridge Institute for Science and Education through an interagency agreement between the U.S. Department of Energy and the National Library of Medicine.
Publisher Copyright:
© The Author 2015. Published by Oxford University Press.
PY - 2016/9/1
Y1 - 2016/9/1
N2 - 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.
AB - 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.
KW - Acquisition
KW - Interoperability
KW - Knowledge discovery
KW - Phenomics
KW - Phenotypes
KW - Semantic representation
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U2 - 10.1093/bib/bbv083
DO - 10.1093/bib/bbv083
M3 - Article
C2 - 26420780
AN - SCOPUS:84995743962
SN - 1467-5463
VL - 17
SP - 819
EP - 830
JO - Briefings in bioinformatics
JF - Briefings in bioinformatics
IS - 5
ER -