Publications

Results 226–250 of 378
Skip to search filters

Multiparameter spectral representation of noise-induced competence in bacillus subtilis

IEEE/ACM Transactions on Computational Biology and Bioinformatics

Sargsyan, Khachik S.; Safta, Cosmin S.; Debusschere, Bert D.; Najm, H.N.

In this work, the problem of representing a stochastic forward model output with respect to a large number of input parameters is considered. The methodology is applied to a stochastic reaction network of competence dynamics in Bacillus subtilis bacterium. In particular, the dependence of the competence state on rate constants of underlying reactions is investigated. We base our methodology on Polynomial Chaos (PC) spectral expansions that allow effective propagation of input parameter uncertainties to outputs of interest. Given a number of forward model training runs at sampled input parameter values, the PC modes are estimated using a Bayesian framework. As an outcome, these PC modes are described with posterior probability distributions. The resulting expansion can be regarded as an uncertain response function and can further be used as a computationally inexpensive surrogate instead of the original reaction model for subsequent analyses such as calibration or optimization studies. Furthermore, the methodology is enhanced with a classification-based mixture PC formulation that overcomes the difficulties associated with representing potentially nonsmooth input-output relationships. Finally, the global sensitivity analysis based on the multiparameter spectral representation of an observable of interest provides biological insight and reveals the most important reactions and their couplings for the competence dynamics. © 2013 IEEE.

More Details
TYPE Journal Article YEAR 2012
ScopusOSTIDOI

Automated exploration of the mechanism of elementary reactions

Najm, H.N.; Zador, Judit Z.

Optimization of new transportation fuels and engine technologies requires the characterization of the combustion chemistry of a wide range of fuel classes. Theoretical studies of elementary reactions — the building blocks of complex reaction mechanisms — are essential to accurately predict important combustion processes such as autoignition of biofuels. The current bottleneck for these calculations is a user-intensive exploration of the underlying potential energy surface (PES), which relies on the “chemical intuition” of the scientist to propose initial guesses for the relevant chemical configurations. For newly emerging fuels, this approach cripples the rate of progress because of the system size and complexity. The KinBot program package aims to accelerate the detailed chemical kinetic description of combustion, and enables large-scale systematic studies on the sub-mechanism level.

More Details
TYPE SAND Report YEAR 2012
OSTIDOI
Results 226–250 of 378
Results 226–250 of 378