@article{raghavan_multi-enps_2019,
	title = {Multi-{ENPS} {Simulator} {Support} {Tool} with {Automatic} {File} {Inter}-conversion and {Multi}-membrane {Execution}},
	issn = {03032647},
	url = {https://linkinghub.elsevier.com/retrieve/pii/S0303264719302278},
	doi = {10.1016/j.biosystems.2019.104067},
	abstract = {P System or Membrane Computing is an unconventional and natural computing model inspired by the functioning of a living cell. This model has an inherently parallel structure. There are several variants of P System developed, each of which has a different application. One of the variants, Enzymatic Numerical P System (ENPS), has primarily been developed to be used with numerical values (as in economics) and thus has vast applications. For realizing ENPS there are several tools available, primarily based on Java and Python, each of which has a different input format. Currently, there is no tool which allows the user to execute ENPS using both the simulators on the same platform, the issue being inter-conversion between input formats, namely, XML and PeP (specific format designed for Python based ENPS). Another major issue with existing simulators is their inability to allow multiple membrane systems to be executed and there is no facility for interconnection between two membrane systems. A tool developed here solves both problems namely, file inter-conversion and multiple membrane support by transferring dependent variable values automatically according to users’ choice. The tool is developed using Python 3.0 and has only a few dependencies. The tool is tested under different scenarios and the results confirm the correctness of the tool.},
	language = {en},
	urldate = {2019-11-12},
	journal = {Biosystems},
	author = {Raghavan, S and Gangadhar, Yashas and Pattar, Varun and Chandrasekaran, K},
	month = nov,
	year = {2019},
	keywords = {Biosystems, Enzymatic Numerical P System, P system, uses sympy},
	pages = {104067},
}

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A tool developed here solves both problems namely, file inter-conversion and multiple membrane support by transferring dependent variable values automatically according to users’ choice. The tool is developed using Python 3.0 and has only a few dependencies. 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