Literature DB >> 16317777

Protein interaction networks of Saccharomyces cerevisiae, Caenorhabditis elegans and Drosophila melanogaster: large-scale organization and robustness.

Dong Li1, Jianqi Li, Shuguang Ouyang, Jian Wang, Songfeng Wu, Ping Wan, Yunping Zhu, Xiaojie Xu, Fuchu He.   

Abstract

High-throughput screens have begun to reveal protein interaction networks in several organisms. To understand the general properties of these protein interaction networks, a systematic analysis of topological structure and robustness was performed on the protein interaction networks of Saccharomyces cerevisiae, Caenorhabditis elegans and Drosophila melanogaster. It shows that the three protein interaction networks have a scale-free and high-degree clustering nature as the consequence of their hierarchical organization. It also shows that they have the small-world property with similar diameter at 4-5. Evaluation of the consequences of random removal of both proteins and interactions from the protein interaction networks suggests their high degree of robustness. Simulation of a protein's removal shows that the protein interaction network's error tolerance is accompanied by attack vulnerability. These fundamental analyses of the networks might serve as a starting point for further exploring complex biological networks and the coming research of "systems biology".

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Year:  2006        PMID: 16317777     DOI: 10.1002/pmic.200500228

Source DB:  PubMed          Journal:  Proteomics        ISSN: 1615-9853            Impact factor:   3.984


  17 in total

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2.  Integrated systems view on networking by hormones in Arabidopsis immunity reveals multiple crosstalk for cytokinin.

Authors:  Muhammad Naseem; Nicole Philippi; Anwar Hussain; Gaby Wangorsch; Nazeer Ahmed; Thomas Dandekar
Journal:  Plant Cell       Date:  2012-05-29       Impact factor: 11.277

3.  Applying modularity analysis of PPI networks to sequenced organisms.

Authors:  Xia Wang; Xianwen Ren; Beiping Li; Junjie Yue; Long Liang
Journal:  Virulence       Date:  2012-08-15       Impact factor: 5.882

4.  Prediction of novel genes associated with negative regulators of toll-like receptors-induced inflammation based on endotoxin tolerance.

Authors:  Yan Yang; Hanxiao Sun; Xuemei Mo; Yi Liu; Hongwei Jia; Xiuying Li; Guang Zhang; Qin Li
Journal:  Inflammation       Date:  2012-12       Impact factor: 4.092

5.  Shadows of complexity: what biological networks reveal about epistasis and pleiotropy.

Authors:  Anna L Tyler; Folkert W Asselbergs; Scott M Williams; Jason H Moore
Journal:  Bioessays       Date:  2009-02       Impact factor: 4.345

6.  Semi-Supervised Multi-View Learning for Gene Network Reconstruction.

Authors:  Michelangelo Ceci; Gianvito Pio; Vladimir Kuzmanovski; Sašo Džeroski
Journal:  PLoS One       Date:  2015-12-07       Impact factor: 3.240

7.  A protein domain co-occurrence network approach for predicting protein function and inferring species phylogeny.

Authors:  Zheng Wang; Xue-Cheng Zhang; Mi Ha Le; Dong Xu; Gary Stacey; Jianlin Cheng
Journal:  PLoS One       Date:  2011-03-24       Impact factor: 3.240

8.  Modularity analysis based on predicted protein-protein interactions provides new insights into pathogenicity and cellular process of Escherichia coli O157:H7.

Authors:  Xia Wang; Junjie Yue; Xianwen Ren; Yuelan Wang; Mingfeng Tan; Beiping Li; Long Liang
Journal:  Theor Biol Med Model       Date:  2011-12-22       Impact factor: 2.432

9.  Infection Strategies of Bacterial and Viral Pathogens through Pathogen-Human Protein-Protein Interactions.

Authors:  Saliha Durmuş Tekir; Tunahan Cakir; Kutlu Ö Ulgen
Journal:  Front Microbiol       Date:  2012-02-14       Impact factor: 5.640

10.  Assessing the druggability of protein-protein interactions by a supervised machine-learning method.

Authors:  Nobuyoshi Sugaya; Kazuyoshi Ikeda
Journal:  BMC Bioinformatics       Date:  2009-08-25       Impact factor: 3.169

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