### Skapa referens, olika format (klipp och klistra)

**Harvard**

Konkoli, Z. (2012) *Modelling reaction noise with a desired accuracy by using the X level Approach Reaction Noise Estimator (XARNES) method*.

** BibTeX **

@article{

Konkoli2012,

author={Konkoli, Zoran},

title={Modelling reaction noise with a desired accuracy by using the X level Approach Reaction Noise Estimator (XARNES) method},

journal={Journal of Theoretical Biology},

issn={0022-5193},

volume={305},

pages={1-14},

abstract={A novel computational framework for modeling reaction noise characteristics has been suggested. The method can be classified as a moment closure method. The approach is based on the concept of correlation forms which are used for describing spatially extended many body problems where particle numbers change in space and time. In here, it was shown how the formalism of spatially extended correlation forms can be adapted to study well mixed reaction systems. Stochastic fluctuations in particle numbers are described by selectively capturing correlation effects up to the desired order, X. The method is referred to as the X-level Approximation Reaction Noise Estimator method (XARNES). For example, X=1 implies the mean field theory (first order effects), the X=2 case corresponds to the previously developed PARNES method (pair effects), etc. The main idea is that inclusion of higher order correlation effects should lead to better (more accurate) results. Three models were used to test the method, two versions of a simple complex formation model, and the Michaelis-Menten model of enzymatic kinetics. It was explicitly demonstrated that increase in X indeed improves accuracy. The approach has been implemented as automatic software using the Mathematica programming language.
The user only needs to input reaction rates, stoichiometry coefficients, and the desired level of computation X.
},

year={2012},

keywords={Well stirred reaction volume; Intracellular noise; XARNES method; Correlation forms},

}

** RefWorks **

RT Journal Article

SR Electronic

ID 146578

A1 Konkoli, Zoran

T1 Modelling reaction noise with a desired accuracy by using the X level Approach Reaction Noise Estimator (XARNES) method

YR 2012

JF Journal of Theoretical Biology

SN 0022-5193

VO 305

SP 1

OP 14

AB A novel computational framework for modeling reaction noise characteristics has been suggested. The method can be classified as a moment closure method. The approach is based on the concept of correlation forms which are used for describing spatially extended many body problems where particle numbers change in space and time. In here, it was shown how the formalism of spatially extended correlation forms can be adapted to study well mixed reaction systems. Stochastic fluctuations in particle numbers are described by selectively capturing correlation effects up to the desired order, X. The method is referred to as the X-level Approximation Reaction Noise Estimator method (XARNES). For example, X=1 implies the mean field theory (first order effects), the X=2 case corresponds to the previously developed PARNES method (pair effects), etc. The main idea is that inclusion of higher order correlation effects should lead to better (more accurate) results. Three models were used to test the method, two versions of a simple complex formation model, and the Michaelis-Menten model of enzymatic kinetics. It was explicitly demonstrated that increase in X indeed improves accuracy. The approach has been implemented as automatic software using the Mathematica programming language.
The user only needs to input reaction rates, stoichiometry coefficients, and the desired level of computation X.

LA eng

DO 10.1016/j.jtbi.2012.04.005

LK http://dx.doi.org/10.1016/j.jtbi.2012.04.005

OL 30