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Gene regulatory networks in plants: learning causality from time and perturbation
- Source :
- Genome Biology, Genome Biology, BioMed Central, 2013, 14 (6), pp.123. ⟨10.1186/gb-2013-14-6-123⟩, Genome Biology 6 (14), . (2013)
- Publication Year :
- 2013
- Publisher :
- HAL CCSD, 2013.
-
Abstract
- International audience; : The goal of systems biology is to generate models for predicting how a system will react under untested conditions or in response to genetic perturbations. This paper discusses experimental and analytical approaches to deriving causal relationships in gene regulatory networks.
- Subjects :
- biologie des systèmes
0106 biological sciences
Gene regulatory networks
network interference
plant
Opinion
Systems biology
Gene regulatory network
Perturbation (astronomy)
Biology
Genes, Plant
Machine learning
computer.software_genre
01 natural sciences
03 medical and health sciences
Artificial Intelligence
Gene Expression Regulation, Plant
[SDV.BV]Life Sciences [q-bio]/Vegetal Biology
030304 developmental biology
Regulation of gene expression
Genetics
0303 health sciences
Models, Genetic
Extramural
business.industry
Quantitative Biology::Molecular Networks
systems biology
Plants
Quantitative Biology::Genomics
Causality
Artificial intelligence
business
computer
Genome, Plant
Signal Transduction
010606 plant biology & botany
Subjects
Details
- Language :
- English
- ISSN :
- 14656906 and 1474760X
- Database :
- OpenAIRE
- Journal :
- Genome Biology, Genome Biology, BioMed Central, 2013, 14 (6), pp.123. ⟨10.1186/gb-2013-14-6-123⟩, Genome Biology 6 (14), . (2013)
- Accession number :
- edsair.doi.dedup.....641c3e8061a06a53de15bf537599015e
- Full Text :
- https://doi.org/10.1186/gb-2013-14-6-123⟩