A Toolbox for Discrete Modelling of Cell Signalling Dynamics

Change log
Paterson, Yasmin Z 
Pleijzier, Markus W 
Piterman, Nir 
Bendtsen, Claus 

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

Cell Cycle, Computational Biology, Computer Simulation, Gene Regulatory Networks, Homeostasis, Humans, Models, Biological, Oscillometry, Signal Transduction, Software, Systems Biology
Journal Title
Integrative Biology (United Kingdom)
Conference Name
Journal ISSN
Volume Title
Volume 10
Oxford University Press (OUP)
Royal Society (Paul Instrument Fund) (UF130039)
MRC (unknown)
Medical Research Council (MC_UU_12022/9)
Biotechnology and Biological Sciences Research Council (1804772)
Royal Society