Antonov Alexey V, Tetko Igor V, Mewes Hans W
GSF National Research Center for Environment and Health, Institute for Bioinformatics, Ingolstädter Landstrasse 1, D-85764 Neuherberg, Germany.
Nucleic Acids Res. 2006 Jan 10;34(1):e6. doi: 10.1093/nar/gnj002.
The development of high-throughput technologies has generated the need for bioinformatics approaches to assess the biological relevance of gene networks. Although several tools have been proposed for analysing the enrichment of functional categories in a set of genes, none of them is suitable for evaluating the biological relevance of the gene network. We propose a procedure and develop a web-based resource (BIOREL) to estimate the functional bias (biological relevance) of any given genetic network by integrating different sources of biological information. The weights of the edges in the network may be either binary or continuous. These essential features make our web tool unique among many similar services. BIOREL provides standardized estimations of the network biases extracted from independent data. By the analyses of real data we demonstrate that the potential application of BIOREL ranges from various benchmarking purposes to systematic analysis of the network biology.
高通量技术的发展催生了对生物信息学方法的需求，以便评估基因网络的生物学相关性。尽管已经提出了几种用于分析一组基因中功能类别的富集情况的工具，但它们都不适用于评估基因网络的生物学相关性。我们提出了一种程序，并开发了一个基于网络的资源（BIOREL），通过整合不同来源的生物学信息来估计任何给定遗传网络的功能偏差（生物学相关性）。网络中边的权重可以是二元的或连续的。这些基本特征使我们的网络工具在许多类似服务中独树一帜。BIOREL提供从独立数据中提取的网络偏差的标准化估计。通过对实际数据的分析，我们证明了BIOREL的潜在应用范围从各种基准测试目的到网络生物学的系统分析。
