The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Functional and topological characterization of protein interaction networks
Abstract
The elucidation of the cell's large‐scale organization is a primary challenge for post‐genomic biology, and understanding the structure of protein interaction networks offers an important starting point for such studies. We compare four available databases that approximate the protein interaction network of the yeast, Saccharomyces cerevisiae, aiming to uncover the network's generic large‐scale properties and the impact of the proteins' function and cellular localization on the network topology. We show how each database supports a scale‐free, topology with hierarchical modularity, indicating that these features represent a robust and generic property of the protein interactions network. We also find strong correlations between the network's structure and the functional role and subcellular localization of its protein constituents, concluding that most functional and/or localization classes appear as relatively segregated subnetworks of the full protein interaction network. The uncovered systematic differences between the four protein interaction databases reflect their relative coverage for different functional and localization classes and provide a guide for their utility in various bioinformatics studies.
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Cites
Emergence of Scaling in Random Networks
Barabási, A.-L., & Albert, R. (1999) · Science · doi:10.1126/science.286.5439.509 · Cited by 36,135
Error and attack tolerance of complex networks
Albert, R., Jeong, H., & Barabási, A.-L. (2000) · Nature · doi:10.1038/35019019 · Cited by 7,534
Self-citationA comprehensive analysis of protein–protein interactions in Saccharomyces cerevisiae
Uetz, P., Giot, L., Cagney, G., Mansfield, T. A., Judson, R. S., Knight, J. R., Lockshon, D., Narayan, V., Srinivasan, M., Pochart, P., et al. (2000) · Nature · doi:10.1038/35001009 · Cited by 4,706
Hierarchical Organization of Modularity in Metabolic Networks
Ravasz, E., Somera, A. L., Mongru, D. A., Oltvai, Z. N., & Barabási, A.-L. (2002) · Science · doi:10.1126/science.1073374 · Cited by 4,224
Self-citationFrom molecular to modular cell biology.
Hartwell, L. H., Hopfield, J. J., Leibler, S., & Murray, A. W. (1999) · Nature · doi:10.1038/35011540 · Cited by 3,632
Cited by
Power-Law Distributions in Empirical Data
Clauset, A., Shalizi, C. R., & Newman, M. E. J. (2009) · SIAM Review · doi:10.1137/070710111 · Cited by 8,019
Network biology: understanding the cell's functional organization
Barabási, A.-L., & Oltvai, Z. N. (2004) · Nature Reviews Genetics · doi:10.1038/nrg1272 · Cited by 7,903
Self-citationA General Framework for Weighted Gene Co-Expression Network Analysis
Zhang, B., & Horvath, S. (2005) · Statistical Applications in Genetics and Molecular Biology · doi:10.2202/1544-6115.1128 · Cited by 5,684
Evaluation of clustering algorithms for protein-protein interaction networks
Brohée, S., & van Helden, J. (2006) · BMC Bioinformatics · doi:10.1186/1471-2105-7-488 · Cited by 892
Ideker, T., & Sharan, R. (2008) · Genome Research · doi:10.1101/gr.071852.107 · Cited by 817
Metadata
- Authors
- Yook, S., Oltvai, Z. N., & Barabási, A.
- Venue
- PROTEOMICS
- Publisher
- Wiley
- Published
- 2004-03-23
- Volume
- 4
- Issue
- 4
- Pages
- 928-942
- ISSN
- 1615-9853 (ISSN-L)
- 1615-9861
- OpenAlex
- W2047693963
- Cited by
- 613
- References
- 5
- FWCI
- 14.21
- Type
- journal article
- Language
- en
- Open access
- closed
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