A Toolbox for Discrete Modelling of Cell Signalling Dynamics

In an age where the volume of data regarding biological systems exceeds our 27 ability to analyse it, many researchers are looking towards systems biology 28 and computational modelling to help unravel the complexities of gene and 29 protein regulatory networks. In particular, the use of discrete modelling allows 30 generation of signalling networks in the absence of full quantitative 31 descriptions of systems, which are necessary for ordinary differential equation 32 (ODE) models. In order to make such techniques more accessible to 33 mainstream researchers, tools such as the BioModelAnalyzer (BMA) have 34 been developed to provide a user-friendly graphical interface for discrete 35 modelling of biological systems. Here we use the BMA to build a library of 36 discrete target functions of known canonical molecular interactions, translated 37 from ordinary differential equations (ODEs). We then show that these BMA 38 target functions can be used to reconstruct complex networks, which can 39 correctly predict many known genetic perturbations. This new library supports 40 the accessibility ethos behind the creation of BMA, providing a toolbox for the 41 construction of complex cell signalling models without the need for extensive 42 experience in computer programming or mathematical modelling, and allows 43 for construction and simulation of complex biological systems with only small 44 amounts of quantitative data

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