Gene expression centered gene regulatory networks studies can provide insight into the dynamics of pathway activities that depend on changes in their environmental conditions. Thus we propose a new pathway analysis approach to detect differentially behaving pathways in abnormal conditions based on G-network theory. Using this approach gene regulatory network model parameters are estimated from normal and abnormal samples using optimization techniques with corresponding constraints. We show that in a ''p53 network'' application, the proposed method effectively detects anomalous activated/inactivated pathways related with MDM2, ATM/ATR and RB1 genes, which could not be observed from previous analyses of gene regulatory network normal and abnormal behaviour.
CITATION STYLE
Kim, H., Atalay, R., & Gelenbe, E. (2011). G-Network Modelling Based Abnormal Pathway Detection in Gene Regulatory Networks. In Computer and Information Sciences II (pp. 257–263). Springer London. https://doi.org/10.1007/978-1-4471-2155-8_32
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