Reimagining What We Measure in Atherosclerosis—a “Phenotype Stack”
Author(s) -
Calum A. MacRae,
Robert M. Califf
Publication year - 2020
Publication title -
circulation research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 4.899
H-Index - 336
eISSN - 1524-4571
pISSN - 0009-7330
DOI - 10.1161/circresaha.120.315941
Subject(s) - biomedicine , phenotype , set (abstract data type) , data science , scale (ratio) , computer science , action (physics) , cognitive psychology , artificial intelligence , computational biology , risk analysis (engineering) , cognitive science , bioinformatics , biology , medicine , psychology , genetics , quantum mechanics , physics , programming language , gene
The term phenotype is so commonly used that we often assume that we each mean the same thing. The general definition, the set of observable characteristics of an individual resulting from the interaction of their genotype with the environment, is often left to the eye of the beholder. Whether applied to the multiple levels of biological phenomena or the intact human being, our ability to characterize, classify, and analyze phenotype has been limited by measurement deficits, computing limitations, and a culture that avoids the generalizable. With the advent of modern technology, there is the potential for a revolution in phenotyping, which incorporates old and new in structured ways to dramatically advance basic understanding of biology and behavior and to lead to major improvements in clinical care and public health. This revolution in how we think about phenotypes will require a radical change in the scale at which biomedicine operates with significant changes in the unit of action, which will have far-reaching implications for how care, translation, and discovery are implemented.
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