title: A cloud-based data network approach for translational cancer research.
abstract: We develop a new model and associated technology for constructing and managing self-organizing data to support translational cancer research studies. We employ a semantic content network approach to address the challenges of managing cancer research data. Such data is heterogeneous, large, decentralized, growing and continually being updated. Moreover, the data originates from different information sources that may be partially overlapping, creating redundancies as well as contradictions and inconsistencies. Building on the advantages of elasticity of cloud computing, we deploy the cancer data networks on top of the CELAR Cloud platform to enable more effective processing and analysis of Big cancer data.
authors.affiliation: Cancer Research UK Manchester Institute, University of Manchester, Manchester, M20 4BX, UK, wei.xing@cruk.manchester.ac.uk.
authors.forename: Wei
authors.initials: W
authors.lastname: Xing
authors.forename: Dimitrios
authors.initials: D
authors.lastname: Tsoumakos
authors.forename: Moustafa
authors.initials: M
authors.lastname: Ghanem
mesh_terms: D019295:Computational Biology / Q000379:methods / Q000706:statistics & numerical data; D057225:Data Mining / Q000379:methods* / Q000706:statistics & numerical data; D006801:Humans; D009369:Neoplasms / Q000175:diagnosis* / Q000628:therapy*; D015203:Reproducibility of Results; D012106:Research / Q000706:statistics & numerical data; D057170:Translational Research, Biomedical / Q000379:methods* / Q000706:statistics & numerical data