Protocol to use TopNet for gene regulatory network modeling using gene expression data from perturbation experiments.
Protocol to use TopNet for gene regulatory network modeling using gene expression data from perturbation experiments.
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DOI：
10.1016/j.xpro.2022.101737
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发表时间：
2022-12-16
期刊：
影响因子：
--
通讯作者：
Mccall, Matthew N.
中科院分区：
文献类型：
--
作者：
Mcmurray, Helene R.;Stern, Harry A.;Land, Aslihan Hartmut;Land, Hartmut;Mccall, Matthew N.
从基因扰动实验推断基因调控网络是研究基因间相互依赖的最可靠方法。在这里，我们描述了初始基因扰动、表达测量和准备步骤，然后使用TopNet进行网络建模。展示了对估计的网络的总结和可视化，以及由网络模型揭示的依赖关系的可选基因测试。虽然TopNet是为基因扰动实验而开发的，但它对节点既被扰动又被测量的数据进行了建模。有关本议定书的使用和执行的完整细节，请参阅。本协议描述了使用扰动数据技术对基因网络进行建模的TopNet算法的使用，以总结和可视化得到的基因网络描述和演示了为TopNet算法生成输入数据所需的实验和生物信息学步骤。描述了网络建模发现的依赖性的基因测试以及实验和计算技术的故障排除的示例提供了出版者注释：进行任何实验协议都需要遵守当地实验室安全和伦理的机构指南。从基因扰动实验推断基因调控网络是研究基因间相互依赖的最可靠方法。在这里，我们描述了初始基因扰动、表达测量和准备步骤，然后使用TopNet进行网络建模。展示了对估计的网络的总结和可视化，以及由网络模型揭示的依赖关系的可选基因测试。虽然TopNet是为基因扰动实验而开发的，但它对节点既被扰动又被测量的数据进行了建模。
Inference of gene regulatory networks from gene perturbation experiments is the most reliable approach for investigating interdependence between genes. Here, we describe the initial gene perturbations, expression measurements, and preparation steps, followed by network modeling using TopNet. Summarization and visualization of the estimated networks and optional genetic testing of dependencies revealed by the network model are demonstrated. While developed for gene perturbation experiments, TopNet models data in which nodes are both perturbed and measured. For complete details on the use and execution of this protocol, please refer to. This protocol describes the use of the TopNet algorithm to model gene networks using perturbation data Techniques to summarize and visualize the resulting gene networks are described and demonstrated Necessary experimental and bioinformatic steps to generate the input data for the TopNet algorithm are described Examples for genetic testing of dependencies uncovered by the network modeling as well as troubleshooting of both experimental and computational techniques are provided Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics. Inference of gene regulatory networks from gene perturbation experiments is the most reliable approach for investigating interdependence between genes. Here, we describe the initial gene perturbations, expression measurements, and preparation steps, followed by network modeling using TopNet. Summarization and visualization of the estimated networks and optional genetic testing of dependencies revealed by the network model are demonstrated. While developed for gene perturbation experiments, TopNet models data in which nodes are both perturbed and measured.
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DOI：
10.1093/bioinformatics/btu239
发表时间：
2014-08-15
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
McCall MN;McMurray HR;Land H;Almudevar A
通讯作者：
Almudevar A
影响因子：
8.8
作者：
McMurray HR;Ambeskovic A;Newman LA;Aldersley J;Balakrishnan V;Smith B;Stern HA;Land H;McCall MN
通讯作者：
McCall MN
DOI：
10.1073/pnas.88.12.5096
发表时间：
1991-06-01
影响因子：
11.1
作者：
JAT, PS;NOBLE, MD;KIOUSSIS, D
通讯作者：
KIOUSSIS, D
影响因子：
16.8
作者：
Xia, Mingxuan;Land, Hartmut
通讯作者：
Land, Hartmut
DOI：
10.1073/pnas.90.2.587
发表时间：
1993-01-15
影响因子：
11.1
作者：
WHITEHEAD, RH;VANEEDEN, PE;JAT, PS
通讯作者：
JAT, PS