How a Quantum Computer Could Quantify Uncertainty in Microkinetic Models.

A method of uncertainty quantification on a quantum circuit using three samples for the Rh(111)-catalyzed CO oxidation reaction is demonstrated. Three parametrized samples of a reduced, linearized microkinetic model populate a single block diagonal matrix for a quantum circuit. This approach leverages the logarithmic scaling of the number of qubits with respect to matrix size.

Multiparameter spectral representation of noise-induced competence in Bacillus subtilis.

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.

Sources of cell-to-cell variability in canonical nuclear factor-κB (NF-κB) signaling pathway inferred from single cell dynamic images.

The canonical nuclear factor-κB (NF-κB) signaling pathway controls a gene network important in the cellular inflammatory response. Upon activation, NF-κB/RelA is released from cytoplasmic inhibitors, from where it translocates into the nucleus, subsequently activating negative feedback loops producing either monophasic or damped oscillatory nucleo-cytoplasmic dynamics. Although the population behavior of the NF-κB pathway has been extensively modeled, the sources of cell-to-cell variability are not well understood.

Identification of viruses using microfluidic protein profiling and Bayesian classification.

We present a rapid method for the identification of viruses using microfluidic chip gel electrophoresis (CGE) of high-copy number proteins to generate unique protein profiles. Viral proteins are solubilized by heating at 95 degrees C in borate buffer containing detergent (5 min), then labeled with fluorescamine dye (10 s), and analyzed using the microChemLab CGE system (5 min). Analyses of closely related T2 and T4 bacteriophage demonstrate sufficient assay sensitivity and peak resolution to distinguish the two phage.