ArticleJournal of the Royal Society, Interface2012
Artefacts in statistical analyses of network motifs: general framework and application to metabolic networks.
Article in Journal of the Royal Society, Interface, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Compression-based inference of network motif sets.PLoS computational biology · 2024Article
- Exploring Emergent Properties in Enzymatic Reaction Networks: Design and Control of Dynamic Functional Systems.Chemical reviews · 2024Review
- Local topological features of robust supply networks.Applied network science · 2022Article
- Two classes of functional connectivity in dynamical processes in networks.Journal of the Royal Society, Interface · 2021Article
- Testing biological network motif significance with exponential random graph models.Applied network science · 2021Article
- Opportunities at the Interface of Network Science and Metabolic Modeling.Frontiers in bioengineering and biotechnology · 2020Review
- Function, dynamics and evolution of network motif modules in integrated gene regulatory networks of worm and plant.Nucleic acids research · 2018Article
- The origin of motif families in food webs.Scientific reports · 2017Article
- Conservation of Species- and Trait-Based Modeling Network Interactions in Extremely Acidic Microbial Community Assembly.Frontiers in microbiology · 2017Article
- Effect of database drift on network topology and enrichment analyses: a case study for RegulonDB.Database : the journal of biological databases and curation · 2016Article
- Network representations and methods for the analysis of chemical and biochemical pathways.Molecular bioSystems · 2013Review
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Authors and funding
6 authors.
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Abstract
Few-node subgraphs are the smallest collective units in a network that can be investigated. They are beyond the scale of individual nodes but more local than, for example, communities. When statistically over- or under-represented, they are called network motifs. Network motifs have been interpreted as building blocks that shape the dynamic behaviour of networks. It is this promise of potentially explaining emergent properties of complex systems with relatively simple structures that led to an interest in network motifs in an ever-growing number of studies and across disciplines. Here, we discuss artefacts in the analysis of network motifs arising from discrepancies between the network under investigation and the pool of random graphs serving as a null model. Our aim was to provide a clear and accessible catalogue of such incongruities and their effect on the motif signature. As a case study, we explore the metabolic network of Escherichia coli and show that only by excluding ever more artefacts from the motif signature a strong and plausible correlation with the essentiality profile of metabolic reactions emerges.
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