Table 1 Models of Gene Regulatory Networks

Differential Equation Models, [5–7]

Require time series data, limited to small-scale networks, quantify interactions, associations are based on mRNA levels

Boolean Networks, [11–13]

Require time series data, limited to small scale networks, associations are based on mRNA levels

Bayesian Networks and Graphical Models, [19–21]

Measure the marginal and conditional dependencies among genes, associations are based on mRNA levels, learning the structure of large scale networks is highly complex

Relevance Networks [16–18]

Measure the linear or nonlinear correlations among genes, associations are based on mRNA levels and may not be direct.

Matrix Decomposition, [27, 28]

Require complete knowledge of a potential connectivity network, refine and quantify the network using gene expression data

Supervised Methods, [35] and this paper

Require partial knowledge of the connectivity network, association are based on activity profile of transcription factors