Dynamical structure analysis of sparsity and minimality heuristics for reconstruction of biochemical networks

— Network reconstruction, i.e. obtaining network structure from input-output information, is a central theme in systems biology. A variety of approaches aim to obtaining structural information from available data. Previous work has introduced dynamical structure functions as a tool for posing and solving the network reconstruction problem. Even for linear time invariant systems, reconstruction requires specific additional information not generated in the typical system identification process. This paper demonstrates that such extra information can be obtained through a limited sequence of system identification experiments on structurally modified systems, analogous to gene silencing and overexpression experiments. In the absence of such extra information, we discuss whether combined assumptions of network sparsity and minimality contribute to the recovery of the network dynamical structure. We provide sufficient conditions for a transfer function to have a completely decoupled m...

• Type: Conference
• Year: 2008
• Where: CDC
• Authors: Russell Howes, Lee John Eccleston, Jorge M. Goncalves, Guy-Bart Stan, Sean Warnick
• Keywords: CDC 2008, Control Systems, Dynamical Structure, Network Reconstruction, Network Structure