Proteins, nucleic acids, and small molecules form a dense network of molecular interactions in a cell.
Molecules are nodes of this network, and the interactions between them are edges. The architecture of
molecular networks can reveal important principles of cellular organization and function, similarly to
the way that protein structure tells us about the function and organization of a protein. Computational
analysis of molecular networks has been primarily concerned with node degree [Wagner, A. & Fell, D.
A. (2001) Proc. R. Soc. London Ser. B 268, 1803-1810; Jeong, H., Tombor, B., Albert, R., Oltvai, Z.
N. & Barabasi, A. L. (2000) Nature 407, 651-654] or degree correlation [Maslov, S. & Sneppen, K.
(2002) Science 296, 910-913], and hence focused on single/two-body properties of these networks.
Here, by analyzing the multibody structure of the network of protein-protein interactions, we
discovered molecular modules that are densely connected within themselves but sparsely connected
with the rest of the network. Comparison with experimental data and functional annotation of genes
showed two types of modules: (i) protein complexes (splicing machinery, transcription factors, etc.)
and (ii) dynamic functional units (signaling cascades, cell-cycle regulation, etc.). Discovered modules
are highly statistically significant, as is evident from comparison with random graphs, and are robust
to noise in the data. Our results provide strong support for the network modularity principle introduced
by Hartwell et al. [Hartwell, L. H., Hopfield, J. J., Leibler, S. & Murray, A. W. (1999) Nature 402,
C47-C52], suggesting that found modules constitute the "building blocks" of molecular networks.
The full text of the paper can be found
here.
This web site contains the lists of complexes and modules found by the methods described in the paper,
the lists of complexes catalogued in the databases, comparisons of our results with experimental complexes,
and predicted novel complexes.
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