Limits...
Hierarchical coordination of periodic genes in the cell cycle of Saccharomyces cerevisiae.

Emmert-Streib F, Dehmer M - BMC Syst Biol (2009)

Bottom Line: No further data are used.This reveals a novel conceptual interpretation of the working mechanism of the cell cycle and the genes regulated by this pathway.Aside from the obtained results for the cell cycle of yeast our approach could be exemplary for the analysis of general pathways by exploiting the rich causal structure of inferred and/or curated gene networks including protein or signaling networks.

View Article: PubMed Central - HTML - PubMed

Affiliation: Center for Cancer Research and Cell Biology, Queen's University Belfast, UK. v@bio-complexity.com

ABSTRACT

Background: Gene networks are a representation of molecular interactions among genes or products thereof and, hence, are forming causal networks. Despite intense studies during the last years most investigations focus so far on inferential methods to reconstruct gene networks from experimental data or on their structural properties, e.g., degree distributions. Their structural analysis to gain functional insights into organizational principles of, e.g., pathways remains so far under appreciated.

Results: In the present paper we analyze cell cycle regulated genes in S. cerevisiae. Our analysis is based on the transcriptional regulatory network, representing causal interactions and not just associations or correlations between genes, and a list of known periodic genes. No further data are used. Partitioning the transcriptional regulatory network according to a graph theoretical property leads to a hierarchy in the network and, hence, in the information flow allowing to identify two groups of periodic genes. This reveals a novel conceptual interpretation of the working mechanism of the cell cycle and the genes regulated by this pathway.

Conclusion: Aside from the obtained results for the cell cycle of yeast our approach could be exemplary for the analysis of general pathways by exploiting the rich causal structure of inferred and/or curated gene networks including protein or signaling networks.

Show MeSH

Related in: MedlinePlus

Information sent from gene A to gene B is transmitted via the shortest path (orange nodes).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC2721836&req=5

Figure 1: Information sent from gene A to gene B is transmitted via the shortest path (orange nodes).

Mentions: Here we assume that the significant (molecular) interaction path follows the shortest paths connecting two genes. This assumption is frequently made [10,35,36] when analyzing gene networks. A motivation for this assumption can be given in form of an optimization argument. Non-shortest paths involve more interactions and, hence, consume more energy and time supposing each interaction consumes in average the same amont of engery and involves the same amont of time. For this reason, communication via shortest paths is not only fastest but also cheapest with respect to engery consumption. Fig. 1 visualizes our assumptions in a simplified network. The nodes shown in orange are on a shortest path connecting gene A and B and information from one gene to another can only be transmitted via causal interactions represented by edges in the network.


Hierarchical coordination of periodic genes in the cell cycle of Saccharomyces cerevisiae.

Emmert-Streib F, Dehmer M - BMC Syst Biol (2009)

Information sent from gene A to gene B is transmitted via the shortest path (orange nodes).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2721836&req=5

Figure 1: Information sent from gene A to gene B is transmitted via the shortest path (orange nodes).
Mentions: Here we assume that the significant (molecular) interaction path follows the shortest paths connecting two genes. This assumption is frequently made [10,35,36] when analyzing gene networks. A motivation for this assumption can be given in form of an optimization argument. Non-shortest paths involve more interactions and, hence, consume more energy and time supposing each interaction consumes in average the same amont of engery and involves the same amont of time. For this reason, communication via shortest paths is not only fastest but also cheapest with respect to engery consumption. Fig. 1 visualizes our assumptions in a simplified network. The nodes shown in orange are on a shortest path connecting gene A and B and information from one gene to another can only be transmitted via causal interactions represented by edges in the network.

Bottom Line: No further data are used.This reveals a novel conceptual interpretation of the working mechanism of the cell cycle and the genes regulated by this pathway.Aside from the obtained results for the cell cycle of yeast our approach could be exemplary for the analysis of general pathways by exploiting the rich causal structure of inferred and/or curated gene networks including protein or signaling networks.

View Article: PubMed Central - HTML - PubMed

Affiliation: Center for Cancer Research and Cell Biology, Queen's University Belfast, UK. v@bio-complexity.com

ABSTRACT

Background: Gene networks are a representation of molecular interactions among genes or products thereof and, hence, are forming causal networks. Despite intense studies during the last years most investigations focus so far on inferential methods to reconstruct gene networks from experimental data or on their structural properties, e.g., degree distributions. Their structural analysis to gain functional insights into organizational principles of, e.g., pathways remains so far under appreciated.

Results: In the present paper we analyze cell cycle regulated genes in S. cerevisiae. Our analysis is based on the transcriptional regulatory network, representing causal interactions and not just associations or correlations between genes, and a list of known periodic genes. No further data are used. Partitioning the transcriptional regulatory network according to a graph theoretical property leads to a hierarchy in the network and, hence, in the information flow allowing to identify two groups of periodic genes. This reveals a novel conceptual interpretation of the working mechanism of the cell cycle and the genes regulated by this pathway.

Conclusion: Aside from the obtained results for the cell cycle of yeast our approach could be exemplary for the analysis of general pathways by exploiting the rich causal structure of inferred and/or curated gene networks including protein or signaling networks.

Show MeSH
Related in: MedlinePlus