We have come to the end of this text. The motivation for writing it is to develop the skills and procedures that are needed to build large-scale kinetic models in the era of availability of massive amounts of high-throughput data, or the so-called omics data types. Historically, kinetic models have been built based on enzymatic information obtained in vitro. Although, many useful dynamic models have been built this way, they are hard to scale and the kinetic constants obtained in vitro may not apply in vivo [32]. An alternative approach is now feasible. The procedures developed here are based on network reconstruction to obtain the stoichiometric matrix and the building of condition-dependent pseudo-elementary mass action kinetics on top of the network structure. A description of the challenges of large-scale model building in the omics era have been outlined [52].

Building dynamic models in the omics era

Workflow The conceptual formulation underlying the MASS model building procedure is summarized in Figure 15.1. It represents an integration of data and mathematical analysis. The workflow that underlies these steps is outlined in Figure 15.2. Briefly, the steps involved in the process are:

1. A model describing the dynamic states of a network requires us to first establish the network to be studied. In the pre-genome era, network reconstruction was based on assembling biochemical data from a variety of sources, e.g., see [107, 120]. Since whole-genome sequencing emerged [121], genome-scale network reconstruction has become possible [29, 30]. There are now a variety of sources to aid with the reconstruction process. The network reconstruction process has been conceptually described [100], the workflows have been laid out [35], and the standard operating procedures detailed [117].

2. […]