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The FLAME-accelerated signalling tool (FaST) is GUI-fronted software that produces agent-based models of signalling pathways. It particularly addresses the computational limitations in agent-based modelling by employing parallelisation on both CPU and GPU-based architecture, without the necessary prerequisite of specialist knowledge of MPI or CUDA coding. FaST takes input files containing species concentrations, diffusion coefficients and reaction kinetics to produce code for an agent-based model, then employs the general agent-based modelling software packages FLAME and FLAME GPU for facile parallelisation. In a related publication, we have demonstrated the methodology used by the tool and the conversion of an ODE-type simulation to agent-based with accurate kinetics and acceleration on both architectures, with a 53.9 × speedup achieved by GPU-parallelisation compared to CPU-serial simulations. This tool is particularly designed to include complex spatial and stochastic into models of cellular signalling processes. The generated code is further fully customisable, whilst retaining the ability to be parallelised.
Systems Biology, Parallelisation, Signalling, Agent-based modelling
Systems Biology, Parallelisation, Signalling, Agent-based modelling
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citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 1 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
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