An approach to evaluate the topological significance of motifs and other patterns in regulatory networks

Goemann, Björn; Wingender, Edgar; Потапов, А. П.

doi:10.1186/1752-0509-3-53

Cited by 15 publications

(17 citation statements)

References 47 publications

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“…patterns made of three vertices. Of particular interest here is the feed-forward loop (FFL) pattern which has been shown previously to be a motif in several transcription networks [4]. By computing the frequency of FFL patterns in the networks analyzed here, we obtained significantly positive Z-scores for this pattern in the transcription, signaling and metabolic network (FFL, pattern 38 in Table 3).…”

Section: Three-node Patterns In the Network Analyzedmentioning

confidence: 72%

“…topological significance, of a pattern instance , n i j P . This influence is quantified by the pairwise disconnectivity index of a pattern instance [4] which is defined as…”

Section: Computation Of the Pairwise Disconnectivity Indexmentioning

confidence: 99%

“…For this purpose, we have proposed a new topological parameter, the pairwise disconnectivity index [3], which is useful in identifying network components that are most critical for the coherence of a network. The methodology may be applied on single nodes or edges, or whole subgraphs such as motifs, as evidenced for transcription networks [4].…”

Section: Introductionmentioning

confidence: 99%

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Comparative Analysis of Topological Patterns in Different Mammalian Networks

Goemann

Потапов

Ante

et al. 2009

Genome Informatics 2009

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We have systematically analyzed various topological patterns comprising 1, 2 or 3 nodes in the mammalian metabolic, signal transduction and transcription networks: These patterns were analyzed with regard to their frequency and statistical over-representation in each network, as well as to their topological significance for the coherence of the networks. The latter property was evaluated using the pairwise disconnectivity index, which we have recently introduced to quantify how critical network components are for the internal connectedness of a network. The 1-node pattern made up by a vertex with a self-loop has been found to exert particular properties in all three networks. In general, vertices with a self-loop tend to be topologically more important than other vertices. Moreover, self-loops have been found to be attached to most 2-node and 3-node patterns, thereby emphasizing a particular role of self-loop components in the architectural organization of the networks. For none of the networks, a positive correlation between the mean topological significance and the Z-score of a pattern could be observed. That is, in general, motifs are not per se more important for the overall network coherence than patterns that are not over-represented. All 2-and 3-node patterns that are over-represented and thus qualified as motifs in all three networks exhibit a loop structure. This intriguing observation can be viewed as an advantage of loop-like structures in building up the regulatory circuits of the whole cell. The transcription network has been found to differ from the other networks in that (i) self-loops play an even higher role, (ii) its binary loops are highly enriched with self-loops attached, and (iii) feedback loops are not over-represented. Metabolic networks reveal some particular topological properties which may reflect the fact that metabolic paths are, to a large extent, reversible. Interestingly, some of the most important 3-node patterns of both the transcription and the signaling network can be concatenated to subnetworks comprising many genes that play a particular role in the regulation of cell proliferation.

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Section: Three-node Patterns In the Network Analyzedmentioning

confidence: 72%

“…topological significance, of a pattern instance , n i j P . This influence is quantified by the pairwise disconnectivity index of a pattern instance [4] which is defined as…”

Section: Computation Of the Pairwise Disconnectivity Indexmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Comparative Analysis of Topological Patterns in Different Mammalian Networks

Goemann

Потапов

Ante

et al. 2009

Genome Informatics 2009

Self Cite

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“…It implies that changes of the network connectivity and/or the particular combination of regulators are balanced by changes of the effective regulation free energy. For example, the connectivity of TF regulatory networks increases for higher organisms (1.2 edges per vertex in E. coli; 1.6 in S. cerevisiae; more than 2 in mammals) (Goemann et al, 2009;Madan Babu and Teichmann, 2003). This increased connectivity within the genomes of higher organisms is consequently expected to be paralleled by smaller effective regulation free energies and/or by a smaller fraction of activators.…”

Section: Gene Expression From Bacteria To Humanmentioning

confidence: 94%

Gene expression density profiles characterize modes of genomic regulation: Theory and experiment

Binder¹,

Wirth²,

Galle³

2010

Journal of Biotechnology

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“…However, the higher frequency of a motif in a network does not necessarily imply that the motif is associated with a particular biochemical function. 61-65 A network motif could be a vestigial structure of the biochemical evolution of organisms. 66 To determine if a motif is associated to a function in a large space of chemical and biochemical networks, it is necessary to use both network analysis and motif mining methods.…”

Section: An Approach To Explore the Network Space To Map Motifs To Fumentioning

confidence: 99%

Network representations and methods for the analysis of chemical and biochemical pathways

2013

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Systems biologists increasingly use network representations to investigate biochemical pathways and their dynamic behaviours. In this critical review, we discuss four commonly used network representations of chemical and biochemical pathways. We illustrate how some of these representations reduce network complexity but result in the ambiguous representation of biochemical pathways. We also examine the current theoretical approaches available to investigate the dynamic behaviour of chemical and biochemical networks. Finally, we describe how the critical chemical and biochemical pathways responsible for emergent dynamic behaviour can be identified using network mining and functional mapping approaches.

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An approach to evaluate the topological significance of motifs and other patterns in regulatory networks

Cited by 15 publications

References 47 publications

Comparative Analysis of Topological Patterns in Different Mammalian Networks

Comparative Analysis of Topological Patterns in Different Mammalian Networks

Gene expression density profiles characterize modes of genomic regulation: Theory and experiment

Network representations and methods for the analysis of chemical and biochemical pathways

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