Identification of Pharmacologically Tractable Protein Complexes in Cancer Using the R-Based Network Clustering and Visualization Program MCODER.

Current multiomics assay platforms facilitate systematic identification of functional entities that are mappable in a biological network, and computational methods that are better able to detect densely connected clusters of signals within a biological network are considered increasingly important....

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Publicado en:BioMed Research International Vol. 2017; pp. 1 - 9
Autores principales: Kwon, Sungjin, Kim, Hyosil, Kim, Hyun Seok
Formato: research tables/charts Journal Article
Publicado: Wiley-Blackwell 6/13/2017
Acceso en línea:Ver este registro en EBSCOhost
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      dt: 6/13/2017
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      pub: Wiley-Blackwell
      place: Malden, Massachusetts
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        10.1155/2017/1016305
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        atl: Identification of Pharmacologically Tractable Protein Complexes in Cancer Using the R-Based Network Clustering and Visualization Program MCODER.
      aug:
        au:
          Kwon, Sungjin
          Kim, Hyosil
          Kim, Hyun Seok
        affil: Graduate Programs for Nanomedical Science, Yonsei University, Seoul, Republic of Korea
      sug:
        subj:
          Proteins Physiology
          Neoplasms Physiopathology
          Metabolic Networks and Pathways
          Human
          Molecular Biology
          Genes
          RNA
          DNA
          Funding Source
      ab: Current multiomics assay platforms facilitate systematic identification of functional entities that are mappable in a biological network, and computational methods that are better able to detect densely connected clusters of signals within a biological network are considered increasingly important. One of the most famous algorithms for detecting network subclusters is Molecular Complex Detection (MCODE). MCODE, however, is limited in simultaneous analyses of multiple, large-scale data sets, since it runs on the Cytoscape platform, which requires extensive computational resources and has limited coding flexibility. In the present study, we implemented the MCODE algorithm in R programming language and developed a related package, which we called MCODER. We found the MCODER package to be particularly useful in analyzing multiple omics data sets simultaneously within the R framework. Thus, we applied MCODER to detect pharmacologically tractable protein-protein interactions selectively elevated in molecular subtypes of ovarian and colorectal tumors. In doing so, we found that a single molecular subtype representing epithelial-mesenchymal transition in both cancer types exhibited enhanced production of the collagen-integrin protein complex. These results suggest that tumors of this molecular subtype could be susceptible to pharmacological inhibition of integrin signaling.
      pubtype: Academic Journal
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        research
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      ougenre: Article
    language: English
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