Metabolism is the essence of life. Metab0lic diseases are very common and cancer has abnormal metabolic phenotype. Metabolic networks are the best understood networks (??! what about moon-lighting and localisation and modification and allostery and ...).
Nodes are substrates edges are reactions.
Modelling Network Function
- Kinetics - small scales need few nodes need ks
- Topological analysis - graph theory - abstract
- Constraints based models - optimisation theory - steady state behaviour.
Treat as series of black boxes with input (medium and nutrients) output is the biomass, we have chemical limits from thermodynamics and the matter constraints.
Multicellular means the different cell metabolisms pass inputs and outputs to each other through the medium between cells. Combine metabolic data with other data which is tissue specific - gene expression and single cell metabolic flux data. Concentrated on gene expression. RNA and protein levels are not well correlated because of translation rate and other factors. Protein level not well correlated to flux depends on degradation allostery etc.
Schuster et al
Fong et al
Look for consistency between flux and the gene expression data based on paths and outputs to check those paths are on that produce the outputs. Can have high expression but the control is at the metabolite level (Fell says this is the general case).