Bittig, Arne T. and Uhrmacher, Adelinde M. (2016) ML-Space: Hybrid Spatial Gillespie and Particle Simulation of Multi-level Rule-based Models in Cell Biology. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 14 (6), pp. 1339-1349. ISSN 1545-5963.
Full text not available from this repository.Abstract
Spatio-temporal dynamics of cellular processes can be simulated at different levels of detail, from (deterministic) partial differential equations via the spatial Stochastic Simulation algorithm to tracking Brownian trajectories of individual particles. We present a spatial simulation approach for multi-level rule-based models, which includes dynamically hierarchically nested cellular compartments and entities. Our approach ML-Space combines discrete compartmental dynamics, stochastic spatial approaches in discrete space, and particles moving in continuous space. The rule-based specification language of ML-Space supports concise and compact descriptions of models and to adapt the spatial resolution of models easily.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Biological system modeling, Computational modeling, Mathematical model, Stochastic processes, Adaptation models, Shape, Syntactics |
