Institute of Bioinformatics and Systems Biology (MIPS), Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany.
PLoS One. 2010 Nov 4;5(11):e13698. doi: 10.1371/journal.pone.0013698.
Gene expression as governed by the interplay of the components of regulatory networks is indeed one of the most complex fundamental processes in biological systems. Although several methods have been published to unravel the hierarchical structure of regulatory networks, weaknesses such as the incorrect or inconsistent assignment of elements to their hierarchical levels, the incapability to cope with cyclic dependencies within the networks or the need for a manual curation to retrieve non-overlapping levels remain unsolved.
METHODOLOGY/RESULTS: We developed HiNO as a significant improvement of the so-called breadth-first-search (BFS) method. While BFS is capable of determining the overall hierarchical structures from gene regulatory networks, it especially has problems solving feed-forward type of loops leading to conflicts within the level assignments. We resolved these problems by adding a recursive correction approach consisting of two steps. First each vertex is placed on the lowest level that this vertex and its regulating vertices are assigned to (downgrade procedure). Second, vertices are assigned to the next higher level (upgrade procedure) if they have successors with the same level assignment and have themselves no regulators. We evaluated HiNO by comparing it with the BFS method by applying them to the regulatory networks from Saccharomyces cerevisiae and Escherichia coli, respectively. The comparison shows clearly how conflicts in level assignment are resolved in HiNO in order to produce correct hierarchical structures even on the local levels in an automated fashion.
We showed that the resolution of conflicting assignments clearly improves the BFS-method. While we restricted our analysis to gene regulatory networks, our approach is suitable to deal with any directed hierarchical networks structure such as the interaction of microRNAs or the action of non-coding RNAs in general. Furthermore we provide a user-friendly web-interface for HiNO that enables the extraction of the hierarchical structure of any directed regulatory network.
HiNO is freely accessible at http://mips.helmholtz-muenchen.de/hino/.
基因表达受调控网络组件相互作用的控制，确实是生物系统中最复杂的基本过程之一。尽管已经发表了几种方法来揭示调控网络的层次结构，但仍存在一些问题未得到解决，如元素被错误或不一致地分配到其层次级别、无法应对网络内的循环依赖关系、或需要手动策展来检索非重叠级别。
方法/结果：我们开发了 HiNO，作为所谓的广度优先搜索（BFS）方法的显著改进。虽然 BFS 能够从基因调控网络中确定整体层次结构，但它在解决前馈类型的循环导致级别分配内的冲突方面尤其存在问题。我们通过添加由两个步骤组成的递归校正方法来解决这些问题。首先，将每个顶点放置在该顶点及其调节顶点所属的最低级别（降级过程）。其次，如果具有相同级别分配的后继者且自身没有调节剂，则将顶点分配到下一个更高的级别（升级过程）。我们通过将 HiNO 与 BFS 方法进行比较，分别将它们应用于酿酒酵母和大肠杆菌的调控网络，来评估 HiNO。比较清楚地表明，HiNO 如何在解决级别分配冲突方面，以自动化方式产生正确的层次结构，即使在局部级别上也是如此。
我们表明，冲突分配的解决明显改进了 BFS 方法。虽然我们将分析限制在基因调控网络上，但我们的方法适用于处理任何有向层次网络结构，例如 microRNAs 的相互作用或一般非编码 RNA 的作用。此外，我们为 HiNO 提供了一个用户友好的网络界面，可用于提取任何有向调控网络的层次结构。
HiNO 可在 http://mips.helmholtz-muenchen.de/hino/ 免费访问。
