Abstract
Biology relies on the central thesis that the genes in an organism encode molecular mechanisms that combine with stimuli and raw materials from the environment to create a final phenotypic expression representative of the genomic programming. While conceptually simple, the genotype-to-phenotype linkage in a eukaryotic organism relies on the interactions of thousands of genes and an environment with a potentially unknowable level of complexity. Modern biology has moved to the use of networks in systems biology to try to simplify this complexity to decode how an organism's genome works. Previously, biological networks were basic ways to organize, simplify, and analyze data. However, recent advances are allowing networks to move beyond description and become phenotypes or hypotheses in their own right. This review discusses these efforts, like mapping responses across biological scales, including relationships among cellular entities, and the direct use of networks as traits or hypotheses.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 840-852 |
| Number of pages | 13 |
| Journal | Trends in Plant Science |
| Volume | 24 |
| Issue number | 9 |
| DOIs | |
| State | Published - Sep 2019 |
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Keywords
- causality
- eigengene
- hypothesis
- network trait
- time course
- visualization
ASJC Scopus subject areas
- Plant Science
Cite this
Plant Networks as Traits and Hypotheses : Moving Beyond Description. / Marshall-Colón, Amy; Kliebenstein, Daniel J.
In: Trends in Plant Science, Vol. 24, No. 9, 09.2019, p. 840-852.Research output: Contribution to journal › Review article
}
TY - JOUR
T1 - Plant Networks as Traits and Hypotheses
T2 - Moving Beyond Description
AU - Marshall-Colón, Amy
AU - Kliebenstein, Daniel J.
PY - 2019/9
Y1 - 2019/9
N2 - Biology relies on the central thesis that the genes in an organism encode molecular mechanisms that combine with stimuli and raw materials from the environment to create a final phenotypic expression representative of the genomic programming. While conceptually simple, the genotype-to-phenotype linkage in a eukaryotic organism relies on the interactions of thousands of genes and an environment with a potentially unknowable level of complexity. Modern biology has moved to the use of networks in systems biology to try to simplify this complexity to decode how an organism's genome works. Previously, biological networks were basic ways to organize, simplify, and analyze data. However, recent advances are allowing networks to move beyond description and become phenotypes or hypotheses in their own right. This review discusses these efforts, like mapping responses across biological scales, including relationships among cellular entities, and the direct use of networks as traits or hypotheses.
AB - Biology relies on the central thesis that the genes in an organism encode molecular mechanisms that combine with stimuli and raw materials from the environment to create a final phenotypic expression representative of the genomic programming. While conceptually simple, the genotype-to-phenotype linkage in a eukaryotic organism relies on the interactions of thousands of genes and an environment with a potentially unknowable level of complexity. Modern biology has moved to the use of networks in systems biology to try to simplify this complexity to decode how an organism's genome works. Previously, biological networks were basic ways to organize, simplify, and analyze data. However, recent advances are allowing networks to move beyond description and become phenotypes or hypotheses in their own right. This review discusses these efforts, like mapping responses across biological scales, including relationships among cellular entities, and the direct use of networks as traits or hypotheses.
KW - causality
KW - eigengene
KW - hypothesis
KW - network trait
KW - time course
KW - visualization
UR - http://www.scopus.com/inward/record.url?scp=85068458145&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85068458145&partnerID=8YFLogxK
U2 - 10.1016/j.tplants.2019.06.003
DO - 10.1016/j.tplants.2019.06.003
M3 - Review article
C2 - 31300195
AN - SCOPUS:85068458145
VL - 24
SP - 840
EP - 852
JO - Trends in Plant Science
JF - Trends in Plant Science
SN - 1360-1385
IS - 9
ER -