Background: 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.
Conclusions: 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.
Availability: HiNO is freely accessible at http://mips.helmholtz-muenchen.de/hino/.
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Evidence ID | Analyze ID | Gene/Complex | Systematic Name/Complex Accession | Qualifier | Gene Ontology Term ID | Gene Ontology Term | Aspect | Annotation Extension | Evidence | Method | Source | Assigned On | Reference |
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Evidence ID | Analyze ID | Gene | Gene Systematic Name | Phenotype | Experiment Type | Experiment Type Category | Mutant Information | Strain Background | Chemical | Details | Reference |
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Evidence ID | Analyze ID | Gene | Gene Systematic Name | Disease Ontology Term | Disease Ontology Term ID | Qualifier | Evidence | Method | Source | Assigned On | Reference |
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Evidence ID | Analyze ID | Regulator | Regulator Systematic Name | Target | Target Systematic Name | Direction | Regulation of | Happens During | Regulator Type | Direction | Regulation Of | Happens During | Method | Evidence | Strain Background | Reference |
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Site | Modification | Modifier | Source | Reference |
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Evidence ID | Analyze ID | Interactor | Interactor Systematic Name | Interactor | Interactor Systematic Name | Allele | Assay | Annotation | Action | Phenotype | SGA score | P-value | Source | Reference | Note |
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Evidence ID | Analyze ID | Interactor | Interactor Systematic Name | Interactor | Interactor Systematic Name | Assay | Annotation | Action | Modification | Source | Reference | Note |
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Complement ID | Locus ID | Gene | Species | Gene ID | Strain background | Direction | Details | Source | Reference |
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Evidence ID | Analyze ID | Dataset | Description | Keywords | Number of Conditions | Reference |
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Evidence ID | Analyze ID | File | Description |
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