Functions for estimating catalytic constant and Michaelis-Menten constant (MM constant) of stochastic Michaelis-Menten enzyme kinetics model are provided. The likelihood functions based on stochastic simulation approximation (SSA), diffusion approximation (DA), and Gaussian processes (GP) are provided to construct posterior functions for the Bayesian estimation. All functions utilize Markov Chain Monte Carlo (MCMC) methods with Metropolis- Hastings algorithm with random walk chain and robust adaptive Metropolis-Hastings algorithm based on Bayesian framework.
| Version: | 0.1.0 |
| Depends: | R (≥ 2.10.0) |
| Imports: | MASS, ramcmc, smfsb, numDeriv |
| Published: | 2018-11-22 |
| Author: | Donghyun Ra, Kyunghoon Kim, Boseung Choi |
| Maintainer: | Donghyun Ra <dongcle72 at gmail.com> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| CRAN checks: | SIfEK results |
| Reference manual: | SIfEK.pdf |
| Package source: | SIfEK_0.1.0.tar.gz |
| Windows binaries: | r-devel: SIfEK_0.1.0.zip, r-release: SIfEK_0.1.0.zip, r-oldrel: SIfEK_0.1.0.zip |
| macOS binaries: | r-release: SIfEK_0.1.0.tgz, r-oldrel: SIfEK_0.1.0.tgz |
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