Hybrid Modeling for Systems Biology: Theory and Practice
I will give an introduction to hybrid modeling methods for bioprocess and biochemical networks modeling. Hybrid methods combine parameter-free modeling with statistical modeling tools. They enable to blend mechanistic knowledge and statistical relationships into models with improved performance and broader scope. Examples of such techniques are hybrid bioreactor modeling for optimisation and control, hybrid metabolic flux analysis for modeling formation of complex recombinant products, metabolic pathway analysis constrained by statistical relationships with “omic” data sets, and reverse envirome-guided metabolic reconstruction without the knowledge of kinetic parameters.
This tutorial aims at (i) giving an overview on theoretical fundaments of hybrid modeling for systems biology and (ii) to provide an introduction to the software tool HYBMOD, a MATLAB toolbox for systems biology hybrid modeling. The presented theoretical methods will be exemplified by examining simulation and experimental case studies.