Transcriptional regulatory network discovery via multiple method integration: application to e. coli KI2

Date

2007-03-30

Author

Sun, Jingjun
Tuncay, Kağan
Haidar, Alaa Abi
Ensman, Lisa
Stanley, Frank
Trelinski, Michael
Ortoleva, Peter

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Transcriptional regulatory network (TRN) discovery from one method (e. g. microarray analysis, gene ontology, phylogenic similarity) does not seem feasible due to lack of sufficient information, resulting in the construction of spurious or incomplete TRNs. We develop a methodology, TRND, that integrates a preliminary TRN, microarray data, gene ontology and phylogenic similarity to accurately discover TRNs and apply the method to E. coli KI2. The approach can easily be extended to include other methodologies. Although gene ontology and phylogenic similarity have been used in the context of gene-gene networks, we show that more information can be extracted when gene-gene scores are transformed to gene-transcription factor (TF) scores using a preliminary TRN. This seems to be preferable over the construction of gene-gene interaction networks in light of the observed fact that gene expression and activity of a TF made of a component encoded by that gene is often out of phase. TRND multi-method integration is found to be facilitated by the use of a Bayesian framework for each method derived from its individual scoring measure and a training set of gene/TF regulatory interactions. The TRNs we construct are in better agreement with microarray data. The number of gene/TF interactions we discover is actually double that of existing networks.

Subject Keywords

Computational Theory and Mathematics, Applied Mathematics, Molecular Biology, Structural Biology

URI

https://hdl.handle.net/11511/40491

Journal

ALGORITHMS FOR MOLECULAR BIOLOGY

DOI

https://doi.org/10.1186/1748-7188-2-2

Collections

Department of Civil Engineering, Article

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Citation Formats

J. Sun et al., “Transcriptional regulatory network discovery via multiple method integration: application to e. coli KI2,” ALGORITHMS FOR MOLECULAR BIOLOGY, pp. 0–0, 2007, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/40491.