A living cell contains thousands of proteins, genes and macromolecules, enmeshed in complex webs of relationships involving direct or indirect contact. At the simplest level, some recurring patterns of interconnections occur more frequently than expected in randomized networks, and these are called 'network motifs'. Lan Zhang from Harvard Medical School, USA, and colleagues found that the concept of 'network themes' recurring complex patterns that encompass multiple occurrences of network motifs allows the building of 'thematic maps' of interactions between macromolecules that can be tied to biological phenomena and may help represent more fundamental network design principles than do simple motifs.
Zhang et al. integrated five different types of biological relationships found in the yeast Saccharomyces cerevisae: protein-protein interactions, genetic interactions, transcriptional regulation, sequence homology and expression correlation. The authors are the first to integrate so many types of data to search for network motifs. The authors conclude that most network motifs found in the integrated S. cerevisae network can be understood in terms of just a few network themes, associated with specific biological phenomena.
Their results also show that thematic maps can highlight previously unknown relationships between functional modules in a cell. In addition, they can be used to predict interactions that are hard to identify experimentally, or to predict the function of genes involved
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