Discovering Distinct Functional Modules of Specific Cancer Types Using Protein-Protein Interaction Networks.
Background. The molecular profiles exhibited in different cancer types are very different; hence, discovering distinct functional modules associated with specific cancer types is very important to understand the distinct functions associated with them. Protein-protein interaction networks carry vita...
| Publicado en: | BioMed Research International Vol. 2015; pp. 1 - 11 |
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| Autores principales: | , , |
| Formato: | algorithm equations & formulas research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
10/1/2015
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=110311212&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 110311212 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 23146133 FT2T jtl: BioMed Research International issn: 23146133 maglogo: N pubinfo: dt: 10/1/2015 vid: 2015 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 110311212 110311212 NLM26495282 110311212 10.1155/2015/146365 NLM26495282 PMC4606133 110311212 ppf: 1 ppct: 10 formats: fmt: @attributes: type: P tig: atl: Discovering Distinct Functional Modules of Specific Cancer Types Using Protein-Protein Interaction Networks. aug: au: Shen, Ru Wang, Xiaosheng Guda, Chittibabu affil: Department of Genetics, Cell Biology and Anatomy, University of Nebraska Medical Center, Omaha, NE 68198, USA sug: subj: Proteins Neoplasms Analysis Cluster Analysis Human ab: Background. The molecular profiles exhibited in different cancer types are very different; hence, discovering distinct functional modules associated with specific cancer types is very important to understand the distinct functions associated with them. Protein-protein interaction networks carry vital information about molecular interactions in cellular systems, and identification of functional modules (subgraphs) in these networks is one of the most important applications of biological network analysis. Results. In this study, we developed a new graph theory based method to identify distinct functional modules from nine different cancer protein-protein interaction networks. The method is composed of three major steps: (i) extracting modules from protein-protein interaction networks using network clustering algorithms; (ii) identifying distinct subgraphs from the derived modules; and (iii) identifying distinct subgraph patterns from distinct subgraphs. The subgraph patterns were evaluated using experimentally determined cancer-specific protein-protein interaction data from the Ingenuity knowledgebase, to identify distinct functional modules that are specific to each cancer type. Conclusion. We identified cancer-type specific subgraph patterns that may represent the functional modules involved in the molecular pathogenesis of different cancer types. Our method can serve as an effective tool to discover cancer-type specific functional modules from large protein-protein interaction networks. pubtype: Academic Journal doctype: algorithm equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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