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MOfinder: a novel algorithm for detecting overlapping modules from protein-protein interaction network.

Yu Q, Li GH, Huang JF - J. Biomed. Biotechnol. (2012)

Bottom Line: We demonstrate that our method is more accurate than other 5 methods.Using the overlapping modules of human PPI network, we constructed the module-module communication network.Our study around overlapping modules suggests a new perspective on the analysis of PPI network and improves our understanding of disease.

View Article: PubMed Central - PubMed

Affiliation: State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China.

ABSTRACT
Since organism development and many critical cell biology processes are organized in modular patterns, many algorithms have been proposed to detect modules. In this study, a new method, MOfinder, was developed to detect overlapping modules in a protein-protein interaction (PPI) network. We demonstrate that our method is more accurate than other 5 methods. Then, we applied MOfinder to yeast and human PPI network and explored the overlapping information. Using the overlapping modules of human PPI network, we constructed the module-module communication network. Functional annotation showed that the immune-related and cancer-related proteins were always together and present in the same modules, which offer some clues for immune therapy for cancer. Our study around overlapping modules suggests a new perspective on the analysis of PPI network and improves our understanding of disease.

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Related in: MedlinePlus

Two overlapping modules shared one protein P08575. The yellow module works on T cell activation and the pink module take part in B cell activation.
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fig9: Two overlapping modules shared one protein P08575. The yellow module works on T cell activation and the pink module take part in B cell activation.

Mentions: To explore the communication between functional modules, we map the functional annotation to each module and evaluate the functional similarity between two overlapping modules. The functional similarity is shown as edge color in Figure 8: the values between 0 and 1 are painted with a pink/blue color gradient, and modules without GO annotation have gray edges. Figure 8(b) gives the functional annotation of modules from the largest cluster in Figure 8(a). Some overlapping modules have the same function, such as the three modules involve in the acetylation of peptidyl-lysine, while several overlapping modules have distinct function, for instance, a module involved in the change of mast cell is overlapping with another module which takes part in the reactions mediated by protein kinases. Figure 9 shows an example of two overlapping modules. One module function is in B-cell activation processes and it contains five proteins: Q15464, O75791, O43561, Q13094, and P08575. The other module (P08575, P20963, P06729, and P06127) involves in T-cell activation. These two Modules share a protein: P08575 (receptor-type tyrosine-protein phosphatase C, CD45), which plays a critical role in receptor-mediated signalling in both B and T-cells [42, 43]. The shared node between two modules suggests a pathway crosstalk between them. Consistent with this hypothesis, several studies have illustrated T-cell-dependent B-cell activation [44].


MOfinder: a novel algorithm for detecting overlapping modules from protein-protein interaction network.

Yu Q, Li GH, Huang JF - J. Biomed. Biotechnol. (2012)

Two overlapping modules shared one protein P08575. The yellow module works on T cell activation and the pink module take part in B cell activation.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3303734&req=5

fig9: Two overlapping modules shared one protein P08575. The yellow module works on T cell activation and the pink module take part in B cell activation.
Mentions: To explore the communication between functional modules, we map the functional annotation to each module and evaluate the functional similarity between two overlapping modules. The functional similarity is shown as edge color in Figure 8: the values between 0 and 1 are painted with a pink/blue color gradient, and modules without GO annotation have gray edges. Figure 8(b) gives the functional annotation of modules from the largest cluster in Figure 8(a). Some overlapping modules have the same function, such as the three modules involve in the acetylation of peptidyl-lysine, while several overlapping modules have distinct function, for instance, a module involved in the change of mast cell is overlapping with another module which takes part in the reactions mediated by protein kinases. Figure 9 shows an example of two overlapping modules. One module function is in B-cell activation processes and it contains five proteins: Q15464, O75791, O43561, Q13094, and P08575. The other module (P08575, P20963, P06729, and P06127) involves in T-cell activation. These two Modules share a protein: P08575 (receptor-type tyrosine-protein phosphatase C, CD45), which plays a critical role in receptor-mediated signalling in both B and T-cells [42, 43]. The shared node between two modules suggests a pathway crosstalk between them. Consistent with this hypothesis, several studies have illustrated T-cell-dependent B-cell activation [44].

Bottom Line: We demonstrate that our method is more accurate than other 5 methods.Using the overlapping modules of human PPI network, we constructed the module-module communication network.Our study around overlapping modules suggests a new perspective on the analysis of PPI network and improves our understanding of disease.

View Article: PubMed Central - PubMed

Affiliation: State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China.

ABSTRACT
Since organism development and many critical cell biology processes are organized in modular patterns, many algorithms have been proposed to detect modules. In this study, a new method, MOfinder, was developed to detect overlapping modules in a protein-protein interaction (PPI) network. We demonstrate that our method is more accurate than other 5 methods. Then, we applied MOfinder to yeast and human PPI network and explored the overlapping information. Using the overlapping modules of human PPI network, we constructed the module-module communication network. Functional annotation showed that the immune-related and cancer-related proteins were always together and present in the same modules, which offer some clues for immune therapy for cancer. Our study around overlapping modules suggests a new perspective on the analysis of PPI network and improves our understanding of disease.

Show MeSH
Related in: MedlinePlus