Send to

Choose Destination
Nat Rev Microbiol. 2010 Oct;8(10):717-29. doi: 10.1038/nrmicro2419. Epub 2010 Aug 31.

Advantages and limitations of current network inference methods.

Author information

Centre of Microbial and Plant Genetics/Bioinformatics, Department of Microbial and Molecular Systems, Katholieke Universiteit Leuven, Leuven, Belgium.


Network inference, which is the reconstruction of biological networks from high-throughput data, can provide valuable information about the regulation of gene expression in cells. However, it is an underdetermined problem, as the number of interactions that can be inferred exceeds the number of independent measurements. Different state-of-the-art tools for network inference use specific assumptions and simplifications to deal with underdetermination, and these influence the inferences. The outcome of network inference therefore varies between tools and can be highly complementary. Here we categorize the available tools according to the strategies that they use to deal with the problem of underdetermination. Such categorization allows an insight into why a certain tool is more appropriate for the specific research question or data set at hand.

[Indexed for MEDLINE]

Supplemental Content

Full text links

Icon for Nature Publishing Group
Loading ...
Support Center