A Novel Method to Verify Multilevel Computational Models of Biological Systems Using Multiscale Spatio-Temporal Meta Model Checking

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Veröffentlicht in:PLoS One vol. 11, no. 5 (May 2016), p. e0154847
1. Verfasser: Pârvu, Ovidiu
Weitere Verfasser: Gilbert, David
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Public Library of Science
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100 1 |a Pârvu, Ovidiu 
245 1 |a A Novel Method to Verify Multilevel Computational Models of Biological Systems Using Multiscale Spatio-Temporal Meta Model Checking 
260 |b Public Library of Science  |c May 2016 
513 |a Journal Article 
520 3 |a Insights gained from multilevel computational models of biological systems can be translated into real-life applications only if the model correctness has been verified first. One of the most frequently employed in silico techniques for computational model verification is model checking. Traditional model checking approaches only consider the evolution of numeric values, such as concentrations, over time and are appropriate for computational models of small scale systems (e.g. intracellular networks). However for gaining a systems level understanding of how biological organisms function it is essential to consider more complex large scale biological systems (e.g. organs). Verifying computational models of such systems requires capturing both how numeric values and properties of (emergent) spatial structures (e.g. area of multicellular population) change over time and across multiple levels of organization, which are not considered by existing model checking approaches. To address this limitation we have developed a novel approximate probabilistic multiscale spatio-temporal meta model checking methodology for verifying multilevel computational models relative to specifications describing the desired/expected system behaviour. The methodology is generic and supports computational models encoded using various high-level modelling formalisms because it is defined relative to time series data and not the models used to generate it. In addition, the methodology can be automatically adapted to case study specific types of spatial structures and properties using the spatio-temporal meta model checking concept. To automate the computational model verification process we have implemented the model checking approach in the software tool Mule (http://mule.modelchecking.org). Its applicability is illustrated against four systems biology computational models previously published in the literature encoding the rat cardiovascular system dynamics, the uterine contractions of labour, the Xenopus laevis cell cycle and the acute inflammation of the gut and lung. Our methodology and software will enable computational biologists to efficiently develop reliable multilevel computational models of biological systems. 
610 4 |a Brunel University 
651 4 |a United Kingdom--UK 
651 4 |a United States--US 
653 |a International conferences 
653 |a Physiology 
653 |a Biological computing 
653 |a Computer science 
653 |a Bioinformatics 
653 |a Biology 
653 |a Computer applications 
653 |a Time series 
653 |a Animal models 
653 |a Organs 
653 |a Cardiovascular system 
653 |a Biological models (mathematics) 
653 |a Coding 
653 |a Computer programs 
653 |a Methodology 
653 |a Environmental 
653 |a Scale (ratio) 
653 |a Multilevel 
653 |a System dynamics 
653 |a Program verification (computers) 
653 |a Uterus 
653 |a Mathematical models 
653 |a Cell cycle 
653 |a Software development tools 
653 |a Lungs 
653 |a Multiscale analysis 
700 1 |a Gilbert, David 
773 0 |t PLoS One  |g vol. 11, no. 5 (May 2016), p. e0154847 
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