Identifying biochemical reaction networks from heterogeneous datasets

— In this paper, we propose a new method to identify biochemical reaction networks (i.e. both reactions and kinetic parameters) from heterogeneous datasets. Such datasets can contain (a) data from several replicates of an experiment performed on a biological system; (b) data measured from a biochemical network subjected to different experimental conditions, for example, changes/perturbations in biological inductions, temperature, gene knock-out, gene over-expression, etc. Simultaneous integration of various datasets to perform system identification has the potential to avoid non-identifiability issues typically arising when only single datasets are used.

• Type: Journal
• Year: 2015
• Where: CDC
• Authors: Wei Pan, Ye Yuan, Lennart Ljung, Jorge M. Gonçalves, Guy-Bart Stan
• Keywords: CDC 2015, Control Systems