利用微阵列表达和序列的整合谱聚类来注释基因功能。

Limin Li, Motoki Shiga, W. Ching, Hiroshi Mamitsuka
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引用次数: 13

摘要

基因注释是后基因组时代的一个基本问题。一个典型的方法是首先根据基因的特征进行聚类,然后在同一聚类中使用已知基因来分配未知基因的功能。大量的基因组信息可用于这个问题,但可以测量任何基因的两种主要类型的数据是微阵列表达和序列,但两者都有自己的缺陷。因此,整合这两个数据源是一种自然而有前途的基因注释方法,特别是考虑到它们在聚类中优化的成本。基于网络模块化的思想,提出了一种基于集成代价的谱聚类的三步基因注释方法。我们从三个不同的角度严格检查了我们提出的方法的性能。所有的实验结果表明,我们的方法优于可能的基于聚类/分类的基因功能注释方法,使用表达式和/或序列。
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Annotating gene functions with integrative spectral clustering on microarray expressions and sequences.
Annotating genes is a fundamental issue in the post-genomic era. A typical procedure for this issue is first clustering genes by their features and then assigning functions of unknown genes by using known genes in the same cluster. A lot of genomic information are available for this issue, but two major types of data which can be measured for any gene are microarray expressions and sequences, both of which however have their own flaws. Thus a natural and promising approach for gene annotation is to integrate these two data sources, especially in terms of their costs to be optimized in clustering. We develop an efficient gene annotation method with three steps containing spectral clustering over the integrated cost, based on the idea of network modularity. We rigorously examined the performance of our proposed method from three different viewpoints. All experimental results indicate the performance advantage of our method over possible clustering/classification-based approaches of gene function annotation, using expressions and/or sequences.
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