Even the simplest biochemical pathway - ligand, receptor, intracellular messenger, output - is far more complex than a simple back-of-the-envelope sketch. Signaling molecules have multiple kinase and phosphatase regulators, and gene promoters can be simultaneously influenced by both positive and negative transcription factors. Ligands, of course, are themselves subject to myriad control systems.
In short, biological systems are not binary entities, in which something is either on or off; they are stochastic, subject to nonlinear behavior.
Fortunately, a range of tools exists to help you build computational models, from the simple to the complex. Here, experts helped us break down the four main classes of computational models, showing how they've made use of the data available.
The simplest type of model is the computational equivalent of that back-of-the-envelope sketch: a network map. Trey Ideker, at the University of California, San Diego, leads one group of researchers that is developing software ...
