Quantitative and logic modelling of molecular and gene networks

Abstract

Computational models of molecular and gene networks are now commonplace. They are becoming larger and more complex, and are based on various approaches. Standard formats permit the sharing and reuse of models for different purposes. Different types of representations of biological processes provide different levels of insight. The choice of representation affects the modelling and simulation methods, as well as the processing of data for model building and validation. A model can be based on prior information gathered from the literature or pathway databases. Alternatively, models can be based on empirical data and the regulatory networks inferred from measurements. Quantitative models can be developed at different levels of granularity, and such simulations provide quantitative temporal predictions. Logic models are increasingly being used in cases in which a lack of quantitative information prevents the use of chemical kinetics approaches. Modelling of entire cells requires the use of modular models based on different approaches and simulation procedures.