Data and model driven hybrid approach to activity scoring of cyclic pathways
Author
Işık, Z.
Atalay V.
Aykanat, Cevdet
Çetin-Atalay, Rengül
Date
2010Source Title
Computer and Information Sciences
Publisher
Springer, Dordrecht
Volume
62
Pages
91 - 94
Language
English
Type
Conference PaperItem Usage Stats
166
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184
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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 graphBiological 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/11693/28524Published Version (Please cite this version)
https://doi.org/10.1007/978-90-481-9794-1_18https://doi.org/10.1007/978-90-481-9794-1