Hy3S
Hy3S -- Hybrid Stochastic Simulation for Supercomputers. Hy3S is now a part of a larger project, SynBioSS, a software suite for synthetic biology. SynBioSS utilizes Hy3S to conduct the simulations, but wraps a cross-platform user interface around it. SynBioSS also includes two web-based pieces of software to help design and create model files for simulation. Continued development of SynBioSS and Hy3S will be documented at the SynBioSS web site. Hy3S (pronounced hi-three-ess) is an open-source project aimed at developing, integrating, and disseminating software that simulates a chemical or biochemical system as quickly as possible, using hybrid or other approximate algorithms to greatly reduce the computational time, but still retain accuracy. We are interested in the computational design of interesting biological devices, especially ones that rely on regulated gene expression to produce useful behavior. By combining quantitatively predictive simulations and design algorithms, one will eventually be able to use computers to identify the exact DNA sequence that produces a desired function, greatly reducing the amount of necessary experimental work. Of course, that goal requires mature simulation algorithms and this project seeks to provide them. When using this software, please cite the following reference: H. Salis, V. Sotiropoulos, Y.N. Kaznessis, BMC Bioinformatics, v7 p93 (2006)
Keywords for this software
References in zbMATH (referenced in 5 articles )
Showing results 1 to 5 of 5.
Sorted by year (- Chen, Minghan; Wang, Shuo; Cao, Yang: Accuracy analysis of hybrid stochastic simulation algorithm on linear chain reaction systems (2019)
- Chevallier, Augustin; Engblom, Stefan: Pathwise error bounds in multiscale variable splitting methods for spatial stochastic kinetics (2018)
- Angius, Alessio; Balbo, Gianfranco; Beccuti, Marco; Bibbona, Enrico; Horvath, Andras; Sirovich, Roberta: Approximate analysis of biological systems by hybrid switching jump diffusion (2015)
- Ilie, Silvana; Jackson, Kenneth R.; Enright, Wayne H.: Adaptive time-stepping for the strong numerical solution of stochastic differential equations (2015)
- Ilie, Silvana; Morshed, Monjur: Adaptive time-stepping using control theory for the chemical Langevin equation (2015)