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The Convergence of Systems and Reductionist Approaches in Complex Trait Analysis
Author(s) -
Evan G. Williams,
Johan Auwerx
Publication year - 2015
Publication title -
cell
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 26.304
H-Index - 776
eISSN - 1097-4172
pISSN - 0092-8674
DOI - 10.1016/j.cell.2015.06.024
Subject(s) - reductionism , phenome , biology , trait , computational biology , systems biology , data science , decipher , genome , genetics , gene , computer science , epistemology , philosophy , programming language
Research into the genetic and environmental factors behind complex trait variation has traditionally been segregated into distinct scientific camps. The reductionist approach aims to decrypt phenotypic variability bit by bit, founded on the underlying hypothesis that genome-to-phenome relations are largely constructed from the additive effects of their molecular players. In contrast, the systems approach aims to examine large-scale interactions of many components simultaneously, on the premise that interactions in gene networks can be both linear and non-linear. Both approaches are complementary, and they are becoming increasingly intertwined due to developments in gene editing tools, omics technologies, and population resources. Together, these strategies are beginning to drive the next era in complex trait research, paving the way to improve agriculture and toward more personalized medicine.

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