Lack of data completeness is a pervasive problem for the analysis of biological networks. One of the main reasons behind this caveat comes from the fact that the experimental approaches to infer the interactions in these networks are highly heterogeneous, in a way that may cause the emergence of systematic experimental-topological correlations.
In this work we study the influence of data incompleteness and quality on some classical results on topological analysis of gene regulatory networks, specially regarding modular structure at different levels.
- J. Sanz, E. Cozzo, J. Borge-Holthoefer, and Y. Moreno, “Topological effects of data incompleteness of gene regulatory networks“, BMC Systems Biology 6:110 (2012). (article).
Further material related to this article:
- Supplementary information: (pdf).
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