The Signing of Regulatory Networks (SIREN) algorithm can infer the regulatory type (positive or negative regulation) of interactions in a known gene regulatory network given corresponding genome-wide gene expression data.
SIREN is an efficient algorithm with low computational complexity; hence, it is applicable to large biological networks. It is a complementary approach for a wide range of network reconstruction methods that do not provide information about the interaction type.
SIREN supports analyzing expression data in two formats:
1. Node columns
One or more node columns of type "floating point" may be used with SIREN. Each node in the network must have a value for each of the selected columns. No missing values are allowed.
2. Tab-delimited text file
This file needs to have one line for each node in the network. The first column is the node id. All subsequent columns are expression values. No missing values are allowed.
After analysis, the app will create a new edge attribute called *SIREN* which indicates the degree of positive or negative regulation between the nodes.
**Reference:**
1) Khosravi P, Gazestani VH, Pirhaji L, Law B, Sadeghi M, Bader GD, Goliaei B (2015) Inferring interaction type in gene regulatory networks using co-expression data. Algorithms Mol Biol 10:23. doi:10.1186/s13015-015-0054-4
2) Montojo J, Khosravi P, Gazestani VH, Bader GD (2015) SIREN Cytoscape plugin: Interaction Type Discrimination in Gene Regulatory Networks. [arXiv:1512.05067 [q-bio.MN]]
