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Biomedical subjects

S E Wildsmith

Publications and source records attributed to S E Wildsmith.

3 recordsLinked to original sources

Multifactorial screening design and analysis of SELDI-TOF ProteinChip array optimization experiments.

Surface-enhanced laser desorption/ionization time-of-flight mass spectrometry is a powerful tool for rapidly generating protein expression data (peptide and protein profiles) from a large number of samples. However, as with any technology, it must be optimized and reproducible for one to have confidence in the results. Using a classical statistical method called the fractional factorial design of experiments, we assessed the effects of 11 different experimental factors. We also developed several metrics that reflect trace quality and reproducibility. These were used to measure the effect of each individual factor, and the interactions between factors, to determine optimal factor settings and thus ultimately produce the best possible traces. Significant improvements to output traces were seen by simultaneously altering several parameters, either in the sample preparation procedure or during the matrix preparation and application procedure. This has led to the implementation of an improved method that gives a better quality, reproducible, and robust output.

Animals↗

Microarrays under the microscope.

Microarray technology is a rapidly advancing area, which is gaining popularity in many biological disciplines from drug target identification to predictive toxicology. Over the past few years, there has been a dramatic increase in the number of methods and techniques available for carrying out this form of gene expression analysis. The techniques and associated peripherals, such as slide types, deposition methods, robotics, and scanning equipment, are undergoing constant improvement, helping to drive the technology forward in terms of robustness and ease of use. These rapid developments, combined with the number of options available and the associated hyperbole, can prove daunting for the new user. This review aims to guide the researcher through the various steps of conducting microarray experiments, from initial strategy to analysing the data, with critical examination of the benefits and disadvantages along the way.

DNA, Complementary↗

Maximization of signal derived from cDNA microarrays.

Microarray technology is a powerful tool for generating expression data on a large number of genes simultaneously. However, as for any assay, it must be reproducible to give confidence in the results. Using a classical statistical method--the factorial design of experiments--we have assessed the effects of different experimental factors in our system. Significant effects on signal were seen when the standard components were substituted with a different enzyme, fluorescent label, or RNA purification method. This has led to the implementation of an improved procedure that maximizes signal without affecting the variability of the system, thus increasing the signal-to-noise ratio. In addition, we were able to quantify the variability between microarrays and replicates within microarrays.

Analysis of Variance↗