Wyniki wyszukiwania - BazTech

Ograniczanie wyników

2 Fundamenta Informaticae

2 2018

Znaleziono wyników: 2

Liczba wyników na stronie

Wyniki wyszukiwania

Sortuj według:

Ogranicz wyniki do:

Discrete-Time Leap Method for Stochastic Simulation

Rohr C.

Fundamenta Informaticae

2018

Vol. 160, nr 1/2

181--198

We present an approach to improve the efficiency of stochastic simulation for large and dense biochemical reaction networks. We use stochastic Petri nets as modelling framework, but the proposed simulation approach is not limited to Petri net representations. The underlying continuous-time Markov chain (CTMC) is converted to an equivalent discrete-time Markov chain (DTMC); this itself gains no efficiency. We improve the efficiency via discrete-time leaps, even though this results in an approximate method. The discrete-time leaps are done by applying the maximum firing rule; this reduces drastically the number of steps. The presented algorithm is implemented in our modelling and simulation tool Snoopy, as well as in our advanced analysis and model checking tool MARCIE. We demonstrate the approach on models of different sizes and complexities.

BioModelKit : Spatial Modelling of Complex Multiscale Molecular Biosystems Based on Modular Models

Blätke M.-A., Rohr C.

Fundamenta Informaticae

2018

Vol. 160, nr 1/2

221--254

Systems and synthetic biology require multiscale biomodel engineering approaches to integrate diverse spatial and temporal scales which will help to better understand and describe the various interactions in biological systems. Our BioModelKit framework for modular biomodel engineering allows composing multiscale models from a set of modules, each describing an individual biomolecular component in the form of a Petri net. In this framework, we now propose a feature for spatial modelling of molecular biosystems. The spatial model represents the coordinates and movement of individual biomolecular components on a defined grid. Here, the distance between components constrains their ability to interact with each other. We use coloured Petri nets to scale the spatial model, such that each molecular component can exist in an arbitrary number of instances. The grid can encode various regular and irregular structures according to the cellular arrangement and geometry. Furthermore, the grid can be divided into compartments to represent the compartmentalisation of the cell.