1. Gene regulatory networks in plants: learning causality from time and perturbation
- Author
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Gabriel Krouk, Amy Marshall Colon, Dennis Shasha, Gloria M. Coruzzi, Jesse M. Lingeman, Biochimie et Physiologie Moléculaire des Plantes (BPMP), Université de Montpellier (UM)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Centre National de la Recherche Scientifique (CNRS), Courant Institute of Mathematical Sciences [New York] (CIMS), New York University [New York] (NYU), NYU System (NYU)-NYU System (NYU), Center for Genomics and Systems Biology, Department of Biology [New York], NYU System (NYU)-NYU System (NYU)-New York University [New York] (NYU), Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), NIH NIGMS GRANT [RO1 GM032877], NSF [MCB-0929338, MCB 1158273], NIH-NRSA [GM095273], ANR [NitroNet: ANR 11 PDOC 020 01], CNRS, and Shasha, Dennis
- 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 - 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.
- Published
- 2013
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