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植物中的基因调控网络：从时间和扰动中学习因果关系。

Gene regulatory networks in plants: learning causality from time and perturbation.

作者信息

Krouk Gabriel, Lingeman Jesse, Colon Amy Marshall, Coruzzi Gloria, Shasha Dennis

出版信息

Genome Biol. 2013 Jun 27;14(6):123. doi: 10.1186/gb-2013-14-6-123.

DOI:10.1186/gb-2013-14-6-123
PMID:23805876
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3707030/
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.

摘要

系统生物学的目标是生成模型，以预测一个系统在未经测试的条件下或对基因扰动做出反应时将如何反应。本文讨论了在基因调控网络中推导因果关系的实验和分析方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ff9c/3707030/9fe0fc0fbb46/gb-2013-14-6-123-1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ff9c/3707030/9fe0fc0fbb46/gb-2013-14-6-123-1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ff9c/3707030/9fe0fc0fbb46/gb-2013-14-6-123-1.jpg

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