Abstract
Analysis of large scale -omics data based on a single tool re- mains ine_cient 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 hy- brid approach to evaluate biological activity of cellular processes. Bio- logical pathway models were taken as graphs and gene scores were trans- ferred through neighbouring nodes of these graphs. An activity score describes the behaviour of a speci_c biological process was computed by owing of converged gene scores until reaching a target process. Biolog- ical 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.
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Işik, Z., Atalay, V., Aykanat, C., Çetin-Atalay, R. (2011). Data and Model Driven Hybrid Approach to Activity Scoring of Cyclic Pathways. In: Gelenbe, E., Lent, R., Sakellari, G., Sacan, A., Toroslu, H., Yazici, A. (eds) Computer and Information Sciences. Lecture Notes in Electrical Engineering, vol 62. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-9794-1_18
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DOI: https://doi.org/10.1007/978-90-481-9794-1_18
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