Using A Kernel P System to Solve The 3-Col Problem

The newly introduced Kernel P systems offer an unitary and elegant way of integrating established features of existing P system variants with new elements with potential value for formal modelling. This paper presents a case study illustrating the expressive power and efficiency of kernel P systems on the 3-Col problem. The use of model checking (in particular of Spin) for formal verification of kernel P systems is also discussed and illustrated in this case.Ministerio de Ciencia e Innovación TIN2009–13192Junta de Andalucía P08–TIC–0420

Kernel P Systems - Version 1

A basic P system, called kernel P system4 (kP system for short), combining features of di erent P systems introduced and studied so far is de ned and discussed. The structure of such systems is de ned as a dynamic graph, similar to tissue-like P systems, the objects are organised as multisets, and the rules in each compartment, rewriting and communication together with system structure changing rules, are applied in accordance with a speci c execution strategy. The de nition of kP systems is introduced and some examples illustrate this concept. Two classes of P systems, namely neural-like and generalised communicating P systems are simulated by kP systems. Some case studies prove the expressive power of these systems.Ministerio de Economía y Competitividad TIN2012-37434Junta de Andalucía P08-TIC-0420

3-Col problem modelling using simple kernel P systems

This paper presents the newly introduced class of (simple) kernel P systems ((s)kP systems) and investigates through a 3-colouring problem case study the expressive power and efficiency of kernel P systems. It describes two skP systems that model the problem and analyses them in terms of efficiency and complexity. The skP models prove to be more succinct (in terms of number of rules, objects, number of cells and execution steps) than the corresponding tissue P system, available in the literature, that solves the same problem, at the expense of a greater length of the rules.Ministerio de Ciencia e Innovación TIN2009–13192Junta de Andalucía P08-TIC-0420

Novel Ground-Up 3D Multicellular Simulators for Synthetic Biology CAD Integrating Stochastic Gillespie Simulations Benchmarked with Topologically Variable SBML Models

The elevation of Synthetic Biology from single cells to multicellular simulations would be a significant scale-up. The spatiotemporal behavior of cellular populations has the potential to be prototyped in silico for computer assisted design through ergonomic interfaces. Such a platform would have great practical potential across medicine, industry, research, education and accessible archiving in bioinformatics. Existing Synthetic Biology CAD systems are considered limited regarding population level behavior, and this work explored the in silico challenges posed from biological and computational perspectives. Retaining the connection to Synthetic Biology CAD, an extension of the Infobiotics Workbench Suite was considered, with potential for the integration of genetic regulatory models and/or chemical reaction networks through Next Generation Stochastic Simulator (NGSS) Gillespie algorithms. These were executed using SBML models generated by in-house SBML-Constructor over numerous topologies and benchmarked in association with multicellular simulation layers. Regarding multicellularity, two ground-up multicellular solutions were developed, including the use of Unreal Engine 4 contrasted with CPU multithreading and Blender visualization, resulting in a comparison of real-time versus batch-processed simulations. In conclusion, high-performance computing and client–server architectures could be considered for future works, along with the inclusion of numerous biologically and physically informed features, whilst still pursuing ergonomic solutions

Blühm, Elger/Kolster, Brigitte/Levin, Helga: Die deutschen Zeitungen des 17. Jahrhunderts

This paper explores the modelling capacities of a new class of P systems, called kernel P systems (kP systems). A specific language for describing kP systems and its translation into Promela, the specification language of Spin, are described. This Promela specification has been further used for simulation and property verification with the Spin model checker. Also, a parallel implementation on GPU parallel architectures, realized using CUDA, is presented and the results are compared with the ones obtained using Promela and Spin. A case study, namely the Subset sum problem, which has been modelled with kernel P systems and further implemented in Promela is presented.Ministerio de Ciencia e Innovación TIN2009–13192Junta de Andalucía P08-TIC-0420