Reconstructing Directed Signed Gene Regulatory Network From Microarray Data
Reconstructing Directed Signed Gene Regulatory Network From Microarray Data
复制标题
DOI：
10.1109/tbme.2011.2163188
复制
发表时间：
2011-12-01
影响因子：
4.6
通讯作者：
Plevritis, Sylvia K.
中科院分区：
文献类型：
--
作者：
Qiu, Peng;Plevritis, Sylvia K.
为了对网络重建算法进行基准测试，人们已经做出了很大的努力来开发重建基因调控网络的算法和模拟基因网络和表达数据的系统。一个有趣的观察是，尽管许多模拟系统选择使用Hill动力学来生成数据，但没有一个重建算法是基于Hill动力学开发的。一种可能的解释是，在Hill动力学中，激活和抑制相互作用采用不同的数学形式，这给重构问题带来了额外的组合复杂性。我们提出了一个新的模型，它的定性行为类似于Hill动力学，但对于激活和抑制具有相同的数学形式。基于这一新模型，我们开发了一种重建基因网络的算法。模拟结果提出了一种新的生物学假说，即在基因敲除实验中，在一定程度上抑制蛋白质合成可能会导致更好的表达数据和更高的网络重构精度。
Great efforts have been made to develop both algorithms that reconstruct gene regulatory networks and systems that simulate gene networks and expression data, for the purpose of benchmarking network reconstruction algorithms. An interesting observation is that although many simulation systems chose to use Hill kinetics to generate data, none of the reconstruction algorithms were developed based on the Hill kinetics. One possible explanation is that, in Hill kinetics, activation and inhibition interactions take different mathematical forms, which brings additional combinatorial complexity into the reconstruction problem. We propose a new model that qualitatively behaves similar to the Hill kinetics, but has the same mathematical form for both activation and inhibition. We developed an algorithm to reconstruct gene networks based on this new model. Simulation results suggested a novel biological hypothesis that in gene knockout experiments, repressing protein synthesis to a certain extent may lead to better expression data and higher network reconstruction accuracy.