G-Network Modelling Based Abnormal Pathway Detection in Gene Regulatory Networks
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.
We would like to thank to Omer Abdelrahman and Zerrin Isik for helpful discussions.
- 2.Beissbarth, T., Speed, T.: GOstat: find statistically overrepresented Gene Ontologies within a group of genes. Bioinformatics 20(9), 1464–1465 (2004)Google Scholar
- 3.Gelenbe, E.: G-networks with triggered customer movement. J. Appl. Probab. 30(3), 742–748 (1993)Google Scholar
- 6.Thattai, M., van Oudenaarden, A.: Intrinsic noise in gene regulatory networks. In: Proceedings of the National Academy of Sciences 98(15), 8614–8619 (2001)Google Scholar