An integrative top-down and bottom-up qualitative model construction framework for exploration of biochemical systems

摘要: Computational modelling of biochemical systems based on top-down and bottom-up approaches has been well studied over the last decade. In this research, after illustrating how to generate atomic components by a set given reactants two user pre-defined component patterns, we propose an integrative approach for stepwise qualitative exploration interactions among in systems. Evolution strategy is applied compose models, simulated annealing employed explore potential models constructed from process. Both support modular addition or subtraction model evolution. Experimental results indicate that our feasible learn relationships qualitatively. addition, hidden target system can be obtained generating complex corresponding composed models. Moreover, qualitatively learned with inferred alternative topologies used further web-lab experimental investigations biologists interest, which may result better understanding system.