Comparative Identification of Differential Interactions from Trajectories of Dynamic Biological Networks

Abstract: It is often challenging to reconstruct accurately a complete dynamic biological network due to the scarcity of data collected in cost-effective experiments. This paper addresses the possibility of comparatively identifying qualitative interaction shifts between two dynamical networks from comparative time course data. An innovative approach is developed to achieve differential interaction detection by statistically comparing the trajectories, instead of numerically comparing the reconstructed interactions. The core of this approach is a statistical heterogeneity test that compares two multiple linear regression equations for the derivatives in nonlinear ordinary differential equations, statistically instead of numerically. In detecting any shift of an interaction, the uncertainty in estimated regression coefficients is taken into account by this test, while it is ignored by the reconstruction-based numerical comparison. The heterogeneity test is accomplished by assessing the ...

• Type: Conference
• Year: 2009
• Where: GCB
• Authors: Zhengyu Ouyang, Mingzhou Song
• Keywords: Biometrics, GCB 2009, Heterogeneity Test, Interaction Shifts, Qualitative Interaction Shifts