71 citations · 405 across the 25 of their papers we have counts for
6 papers · 1 filter
Bond Graph Modelling of Chemoelectrical Energy Transduction
Peter J. Gawthrop, Ivo Siekmann, Tatiana Kameneva +3
Energy-based bond graph modelling of biomolecular systems is extended to include chemoelectrical trans- duction thus enabling integrated thermodynamically-compliant modelling of ch…
Modular Bond-graph Modelling and Analysis of Biomolecular Systems
Peter Gawthrop, Edmund Crampin
Bond graphs can be used to build thermodynamically-compliant hierarchical models of biomolecular systems. As bond graphs have been widely used to model, analyse and synthesise engi…
Data-driven modelling of the inositol trisphosphate receptor (IPR) and its role in calcium induced calcium release (CICR)
Ivo Siekmann, Pengxing Cao, James Sneyd +1
We give a review of the current state of the art of data-driven modelling of the inositol trisphosphate receptor (IPR). After explaining that the IPR plays a crucial role as a cent…
Gene expression modelling across multiple cell-lines with MapReduce
David M. Budden, Edmund J. Crampin
With the wealth of high-throughput sequencing data generated by recent large-scale consortia, predictive gene expression modelling has become an important tool for integrative anal…
Hierarchical Bond Graph Modelling of Biochemical Networks
Peter J. Gawthrop, Joseph Cursons, Edmund J. Crampin
The bond graph approach to modelling biochemical networks is extended to allow hierarchical construction of complex models from simpler components. This is made possible by represe…
TREEOME: A framework for epigenetic and transcriptomic data integration to explore regulatory interactions controlling transcription
David M Budden, Daniel G Hurley, Edmund J Crampin
Motivation: Predictive modelling of gene expression is a powerful framework for the in silico exploration of transcriptional regulatory interactions through the integration of high…