David J Bakewell | Search PubMed

PubMed2006

Dielectrophoresis of DNA: time- and frequency-dependent collections on microelectrodes.

This paper reports measurements that characterize the collection of DNA onto interdigitated microelectrodes by high-frequency dielectrophoresis. Measurements of time-dependent collection of 12 kilobase pair plasmid DNA onto microelectrodes by dielectrophoresis show significant reduction in the response as the frequency increases from 100 kHz to 20 MHz. Collection time profiles are quantitatively measured using fluorescence microscopy over the range 100 kHz to 5 MHz and are represented in terms of two parameters: the initial dielectrophoretic collection rate, and the initial to steady-state collection transition. Measured values for both parameters are consistent with trends in the frequency-dependent real part of the effective polarizability measured for the same plasmid DNA using dielectric spectroscopy. The experimentally measured parameters are qualitatively compared with trends predicted by theory that takes into account dielectrophoretic particle movement and diffusion. The differences between experiment and theory are discussed with suggested improvements to theoretical models, for example, including the effects of electrohydrodynamically driven fluid motion.

Computer Simulation↗

PubMed2004

Weighted analysis of microarray gene expression using maximum-likelihood.

MOTIVATION: The numerical values of gene expression measured using microarrays are usually presented to the biological end-user as summary statistics of spot pixel data, such as the spot mean, median and mode. Much of the subsequent data analysis reported in the literature, however, uses only one of these spot statistics. This results in sub-optimal estimates of gene expression levels and a need for improvement in quantitative spot variation surveillance. RESULTS: This paper develops a maximum-likelihood method for estimating gene expression using spot mean, variance and pixel number values available from typical microarray scanners. It employs a hierarchical model of variation between and within microarray spots. The hierarchical maximum-likelihood estimate (MLE) is shown to be a more efficient estimator of the mean than the 'conventional' estimate using solely the spot mean values (i.e. without spot variance data). Furthermore, under the assumptions of our model, the spot mean and spot variance are shown to be sufficient statistics that do not require the use of all pixel data. The hierarchical MLE method is applied to data from both Monte Carlo (MC) simulations and a two-channel dye-swapped spotted microarray experiment. The MC simulations show that the hierarchical MLE method leads to improved detection of differential gene expression particularly when 'outlier' spots are present on the arrays. Compared with the conventional method, the MLE method applied to data from the microarray experiment leads to an increase in the number of differentially expressed genes detected for low cut-off P-values of interest.

Algorithms↗