It works by building an initial model of all possible functional equations, simplifying the model, and selecting the best parameters for the simplified model.
Building an initial model in the electron density (ED) map has been automated to a significant extent, with software like ARP/wARP (Langer et al., 2008), Resolve (Terwilliger, 2003), Buccaneer (Cowtan, 2006) and others, but the final steps in model building and refinement are typically left to the user.
For the Nordex tower, the model updating was achieved through building an initial three-dimensional FE model in ANSYS, which was then modified in successive steps to finally match the measured properties with good agreement.
Phenix.autobuild was used to build an initial model of DC-LAMP but succeeded only in building parts of one of the two molecules in the asymmetric unit.
Here we have considered the model-building cycle where an initial model, based on existing data and a priori knowledge of the system, is subsequently refined by hypotheses-driven iterations (see Figure 11).
The process of building a model of a biological system typically starts by generating an initial model candidate, or by taking one from the pre-existing knowledge, and then involves an iterative cycle of hypotheses-driven model modifications, new experimentation and subsequent model identification steps, finally leading to a satisfactory refined model [ 6, 7].
After an initial model-building phase, the first-order approximation to the likelihood available in NONMEM was used to model the data.
In building the initial model of LY30 effects, we interpolated from a few measured time points of cFLIP, to obtain a simple approximation of LY30-induced decay of cFLIP, using a constant degradation rate (Supplementary Material 1.4).
To overcome all those difficulties, we deeply investigated the KGML documents, as well as the content of all cross-linked KEGG databases, and developed strategies for building useful initial models in SBML and BioPAX.
The flowchart of our work is presented in Figure 1 and mainly consists of six steps: constructing an initial IRN, simplifying the initial network, building a mathematical model, estimating parameters in the model with the DE algorithm, significance test and sensitivity analysis for the regulations, and performing an enrichment analysis.
