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      • Faculty of Engineering
      • Department of Computer Engineering
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      Data and model driven hybrid approach to activity scoring of cyclic pathways

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      Author
      Işık, Z.
      Atalay V.
      Aykanat, Cevdet
      Çetin-Atalay, Rengül
      Date
      2010
      Source Title
      Computer and Information Sciences
      Publisher
      Springer, Dordrecht
      Volume
      62
      Pages
      91 - 94
      Language
      English
      Type
      Conference Paper
      Item Usage Stats
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      Abstract
      Analysis of large scale -omics data based on a single tool remains inefficient to reveal molecular basis of cellular events. Therefore, data integration from multiple heterogeneous sources is highly desirable and required. In this study, we developed a data- and model-driven hybrid approach to evaluate biological activity of cellular processes. Biological pathway models were taken as graphs and gene scores were transferred through neighbouring nodes of these graphs. An activity score describes the behaviour of a specific biological process was computed by owing of converged gene scores until reaching a target process. Biological pathway model based approach that we describe in this study is a novel approach in which converged scores are calculated for the cellular processes of a cyclic pathway. The convergence of the activity scores for cyclic graphs were demonstrated on the KEGG pathways. © 2011 Springer Science+Business Media B.V.
      Keywords
      AS graph
      Biological activities
      Biological pathways
      Biological process
      Cellular events
      Cellular process
      Cyclic graph
      Data integration
      Heterogeneous sources
      Hybrid approach
      Model based approach
      Model-driven
      Molecular basis
      Neighbouring nodes
      Genes
      Information science
      Permalink
      http://hdl.handle.net/11693/28524
      Published Version (Please cite this version)
      https://doi.org/10.1007/978-90-481-9794-1_18
      https://doi.org/10.1007/978-90-481-9794-1
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      • Department of Computer Engineering 1368
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