{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,28]],"date-time":"2025-10-28T18:14:56Z","timestamp":1761675296376},"reference-count":26,"publisher":"World Scientific Pub Co Pte Ltd","issue":"04","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Advs. Complex Syst."],"published-print":{"date-parts":[[2005,12]]},"abstract":"<jats:p>We employ the random graph theory approach to analyze the protein\u2013protein interaction database DIP. Several global topological parameters are used to characterize the protein\u2013protein interaction networks (PINs) for seven organisms. We find that the seven PINs are well approximated by the scale-free networks, that is, the node degree cumulative distribution P<jats:sub>cum<\/jats:sub>(k) scales with the node degree k (P<jats:sub>cum<\/jats:sub>(k) ~ k<jats:sup>-\u03b1<\/jats:sup>). We also find that the logarithm of the average clustering coefficient C<jats:sub>ave<\/jats:sub>(k) scales with k (C<jats:sub>ave<\/jats:sub>(k) ~ k<jats:sup>-\u03b2<\/jats:sup>), for E. coli and S. cerevisiae. In particular, we determine that the E. coli and the S. cerevisiae PINs are better represented by the stochastic and deterministic hierarchical network models, respectively. The current fruit fly protein\u2013protein interaction dataset does not have convincing evidence in favor of the hierarchical network model. These findings lead us to conclude that, in contrast to scale-free structure, hierarchical structure model applies for certain species' PINs only.<\/jats:p><jats:p>We also demonstrate that PINs are robust when subject to random perturbation where up to 50% of the nodes are rewired. Average node degree correlation study supports the fact that nodes of low connectivity are correlated, whereas nodes of high connectivity are not directly linked.<\/jats:p>","DOI":"10.1142\/s0219525905000531","type":"journal-article","created":{"date-parts":[[2006,1,5]],"date-time":"2006-01-05T00:48:36Z","timestamp":1136422116000},"page":"383-397","source":"Crossref","is-referenced-by-count":4,"title":["HIERARCHICAL AND TOPOLOGICAL STUDY OF THE PROTEIN\u2013PROTEIN INTERACTION NETWORKS"],"prefix":"10.1142","volume":"08","author":[{"given":"PO-HAN","family":"LEE","sequence":"first","affiliation":[{"name":"The Affiliated Senior High School of National Taiwan Normal University, 143, Hsin-Yi Road, Sec 3, Taipei, Taiwan 106, ROC"}]},{"given":"CHIEN-HUNG","family":"HUANG","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Information Engineering, National Formosa University, 64, Wen-Hwa Road, Hu-wei, Yun-Lin, Taiwan 632, ROC"}]},{"given":"JYWE-FEI","family":"FANG","sequence":"additional","affiliation":[{"name":"Department of Digital Content and Technology, National Taichung Teachers College, 140, Min Sheng Road, Taichung, Taiwan 403, ROC"}]},{"given":"HSIANG-CHUAN","family":"LIU","sequence":"additional","affiliation":[{"name":"Department of Biotechnology and Bioinformatics, Asia University, No.500, Lioufeng Road, Wufeng Shiang, Taichung, Taiwan 413, ROC"}]},{"given":"KA-LOK","family":"NG","sequence":"additional","affiliation":[{"name":"Department of Biotechnology and Bioinformatics, Asia University, No.500, Lioufeng Road, Wufeng Shiang, Taichung, Taiwan 413, ROC"}]}],"member":"219","published-online":{"date-parts":[[2012,3,16]]},"reference":[{"key":"rf1","doi-asserted-by":"publisher","DOI":"10.1103\/RevModPhys.74.47"},{"key":"rf2","doi-asserted-by":"publisher","DOI":"10.1016\/S0014-5793(02)03427-0"},{"key":"rf3","doi-asserted-by":"publisher","DOI":"10.1038\/nrg1272"},{"key":"rf4","doi-asserted-by":"publisher","DOI":"10.1074\/mcp.M100037-MCP200"},{"key":"rf5","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevE.65.066122"},{"key":"rf6","doi-asserted-by":"publisher","DOI":"10.1093\/acprof:oso\/9780198515906.001.0001"},{"key":"rf7","first-page":"17","volume":"5","author":"Erdos P.","journal-title":"Publ. 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