Detection of Regulatory Circuits by Integrating the Cellular Networks of Protein-protein Interactions and Transcription Regulation
The post-genomic era is marked by huge amounts of data generated by
large-scale functional genomic and proteomic experiments. A major
challenge is to integrate the various types of genome-scale information
in order to reveal the intra- and inter-relationships between genes
and proteins that constitute a living cell. We present a novel
application of classical graph algorithms to integrate the cellular
networks of protein-protein interactions and transcription regulation.
We demonstrate how integration of these two networks enables the
discovery of simple as well as complex regulatory circuits that
involve both protein-protein and protein-DNA interactions.
These circuits may serve for positive or negative feedback mechanisms.
By applying our approach to data from the yeast Saccharomyces
cerevisiae we were able to identify known simple and complex regulatory
circuits and to discover many putative circuits, whose biological relevance
has been assessed using various types of experimental data. The newly
identified relations provide new insight into the processes that take place
in the cell, insight that could not be gained by analyzing each type of
data independently. The computational scheme that we propose may be used
to integrate additional functional genomic and proteomic data and to reveal
other types of relations, in yeast as well as in higher organisms.