Higa Carlos Ha, Louzada Vitor Hp, Andrade Tales P, Hashimoto Ronaldo F
Institute of Mathematics and Statistics, University of Sao Paulo, Rua do Matao 1010, 05508-090, Sao Paulo - SP, Brazil.
BMC Proc. 2011 May 28;5 Suppl 2(Suppl 2):S5. doi: 10.1186/1753-6561-5-S2-S5.
A popular model for gene regulatory networks is the Boolean network model. In this paper, we propose an algorithm to perform an analysis of gene regulatory interactions using the Boolean network model and time-series data. Actually, the Boolean network is restricted in the sense that only a subset of all possible Boolean functions are considered. We explore some mathematical properties of the restricted Boolean networks in order to avoid the full search approach. The problem is modeled as a Constraint Satisfaction Problem (CSP) and CSP techniques are used to solve it.
We applied the proposed algorithm in two data sets. First, we used an artificial dataset obtained from a model for the budding yeast cell cycle. The second data set is derived from experiments performed using HeLa cells. The results show that some interactions can be fully or, at least, partially determined under the Boolean model considered.
The algorithm proposed can be used as a first step for detection of gene/protein interactions. It is able to infer gene relationships from time-series data of gene expression, and this inference process can be aided by a priori knowledge available.
基因调控网络的一种流行模型是布尔网络模型。在本文中，我们提出了一种算法，用于使用布尔网络模型和时间序列数据对基因调控相互作用进行分析。实际上，布尔网络存在局限性，即只考虑了所有可能布尔函数的一个子集。我们探索受限布尔网络的一些数学性质，以避免全搜索方法。该问题被建模为一个约束满足问题（CSP），并使用CSP技术来解决它。
我们将所提出的算法应用于两个数据集。首先，我们使用了一个从芽殖酵母细胞周期模型获得的人工数据集。第二个数据集来自使用HeLa细胞进行的实验。结果表明，在所考虑的布尔模型下，一些相互作用可以被完全或至少部分确定。
所提出的算法可作为检测基因/蛋白质相互作用的第一步。它能够从基因表达的时间序列数据中推断基因关系，并且这个推断过程可以借助现有的先验知识得到辅助。
