Finding optimal gene networks using biological constraints.
Finding optimal gene networks using biological constraints.
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DOI：
10.11234/gi1990.14.124
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发表时间：
2003
期刊：
影响因子：
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通讯作者：
S. Ott;S. Miyano
中科院分区：
文献类型：
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作者：
S. Ott;S. Miyano
从基因表达测量中准确估计基因网络是生物信息学领域的一大挑战。由于估计基因网络的问题是NP困难的，并且呈现出超指数大小的搜索空间，研究人员正在使用启发式算法来完成这项任务。然而，关于启发式估计的准确性几乎没有什么可说的。为了克服这一问题，我们提出了一种通用的方法，将搜索空间缩减为具有生物意义的子空间，并在子空间内在线性时间内找到最优解。我们在酵母和枯草芽孢杆菌数据的应用中展示了这种方法的有效性。
The accurate estimation of gene networks from gene expression measurements is a major challenge in the field of Bioinformatics. Since the problem of estimating gene networks is NP-hard and exhibits a search space of super-exponential size, researchers are using heuristic algorithms for this task. However, little can be said about the accuracy of heuristic estimations. In order to overcome this problem, we present a general approach to reduce the search space to a biologically meaningful subspace and to find optimal solutions within the subspace in linear time. We show the effectiveness of this approach in application to yeast and Bacillus subtilis data.