Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10234725 | Metabolic Engineering | 2005 | 11 Pages |
Abstract
Interaction among different signalling pathways has been noted repeatedly. However, no systematic method has been developed to identify and quantify such interactions. Here we reported that network component analysis (NCA) was able to determine interactions among various signalling pathways in Escherichia coli K-12 based on known transcription factor (TF)-promoter connectivity information and microarray data from genetic knockout strains. The TF activities determined from NCA allow the quantitation of functional interactions, barring gross errors in the connectivity and microarray data. By using a robust statistical test, 37 pairs of functional interactions were identified. Eighteen interaction pairs confirmed previous implications, while 19 others represent new predictions. These results demonstrate that the functional interactions among various signalling pathways may be rather significant. With reasonable TF-promoter connectivity, NCA coupled with genetic knockouts and microarray experiments provides a systematic way to elucidate interaction networks. As this approach cannot distinguish between cross-talks and unidentified direct regulation, the results should provide incentives for further experimental testing.
Related Topics
Physical Sciences and Engineering
Chemical Engineering
Bioengineering
Authors
Young-Lyeol Yang, James C. Liao,