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On the origin of distribution patterns of motifs in biological networks.

Konagurthu AS, Lesk AM - BMC Syst Biol (2008)

Bottom Line: The inference that these motifs have been selected for function rests on the idea that their occurrences are significantly more frequent than random.Indeed, certain topological features of biological networks give rise naturally to the common appearance of the motifs.We therefore question whether frequencies of occurrences are reasonable evidence that the structures of motifs have been selected for their functional contribution to the operation of networks.

View Article: PubMed Central - HTML - PubMed

Affiliation: The Huck Institute for Genomics, Proteomics, and Bioinformatics, Department of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, PA 16802, USA. arun@bx.psu.edu

ABSTRACT

Background: Inventories of small subgraphs in biological networks have identified commonly-recurring patterns, called motifs. The inference that these motifs have been selected for function rests on the idea that their occurrences are significantly more frequent than random.

Results: Our analysis of several large biological networks suggests, in contrast, that the frequencies of appearance of common subgraphs are similar in natural and corresponding random networks.

Conclusion: Indeed, certain topological features of biological networks give rise naturally to the common appearance of the motifs. We therefore question whether frequencies of occurrences are reasonable evidence that the structures of motifs have been selected for their functional contribution to the operation of networks.

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Self-Assemblies of two FFLs. Various possible self-assemblies of two FFLs sharing a common edge.
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Figure 2: Self-Assemblies of two FFLs. Various possible self-assemblies of two FFLs sharing a common edge.

Mentions: Kashtan and colleagues [16] observed that regulatory networks contain multi-output FFL generalizations (see Figure 2(a)) in frequencies much higher than multi-input (Figure 2(d)) and multi-intermediate (Figure 2(f)) generalisations. (These authors also suggested that multi-output FFLs were selected to achieve some information processing role [16].)


On the origin of distribution patterns of motifs in biological networks.

Konagurthu AS, Lesk AM - BMC Syst Biol (2008)

Self-Assemblies of two FFLs. Various possible self-assemblies of two FFLs sharing a common edge.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2538512&req=5

Figure 2: Self-Assemblies of two FFLs. Various possible self-assemblies of two FFLs sharing a common edge.
Mentions: Kashtan and colleagues [16] observed that regulatory networks contain multi-output FFL generalizations (see Figure 2(a)) in frequencies much higher than multi-input (Figure 2(d)) and multi-intermediate (Figure 2(f)) generalisations. (These authors also suggested that multi-output FFLs were selected to achieve some information processing role [16].)

Bottom Line: The inference that these motifs have been selected for function rests on the idea that their occurrences are significantly more frequent than random.Indeed, certain topological features of biological networks give rise naturally to the common appearance of the motifs.We therefore question whether frequencies of occurrences are reasonable evidence that the structures of motifs have been selected for their functional contribution to the operation of networks.

View Article: PubMed Central - HTML - PubMed

Affiliation: The Huck Institute for Genomics, Proteomics, and Bioinformatics, Department of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, PA 16802, USA. arun@bx.psu.edu

ABSTRACT

Background: Inventories of small subgraphs in biological networks have identified commonly-recurring patterns, called motifs. The inference that these motifs have been selected for function rests on the idea that their occurrences are significantly more frequent than random.

Results: Our analysis of several large biological networks suggests, in contrast, that the frequencies of appearance of common subgraphs are similar in natural and corresponding random networks.

Conclusion: Indeed, certain topological features of biological networks give rise naturally to the common appearance of the motifs. We therefore question whether frequencies of occurrences are reasonable evidence that the structures of motifs have been selected for their functional contribution to the operation of networks.

Show MeSH