@article{f170f947ff5d4954bef2c52f735a8022,
title = "Gene regulatory networks in plants: Learning causality from time and perturbation",
abstract = "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.",
keywords = "Gene regulatory networks, Network interference, Plant, Systems biology",
author = "Gabriel Krouk and Jesse Lingeman and Colon, {Amy Marshall} and Gloria Coruzzi and Dennis Shasha",
note = "Funding Information: This work is supported by NIH NIGMS GRANT RO1 GM032877, NSF Grants MCB-0929338 and MCB 1158273 to GC and DS; by NIH-NRSA GM095273 to AMC; grants from ANR (NitroNet: ANR 11 PDOC 020 01) and CNRS (PEPS Bio math Info 2012-2013: SuperRegNet) to GK. We thank Becca Susko for her outstanding work on the manuscript preparation, and Benoit Lacombe and Sandrine Ruffel for critical reading and help. Publisher Copyright: {\textcopyright} 2013 BioMed Central Ltd.",
year = "2013",
month = jun,
day = "27",
doi = "10.1186/gb-2013-14-6-123",
language = "English (US)",
volume = "14",
journal = "Genome biology",
issn = "1474-7596",
publisher = "BioMed Central",
number = "6",
}