Optimization of gold nanoparticle-based DNA detection for microarrays.

DNA microarrays are promising tools for fast and highly parallel DNA detection by means of fluorescence or gold nanoparticle labeling. However, substrate modification with silanes (as a prerequisite for capture DNA binding) often leads to inhomogeneous surfaces and/or nonspecific binding of the labeled DNA. We examined both different substrate cleaning and activating protocols and also different blocking strategies for optimizing the procedures, especially those for nanoparticle labeling.

Characterisation of lithographically patterned organosilane monolayers by preferential adsorption of dye molecules.

A method for the visualisation of micropatterned spots of molecular organosilane monolayers by adsorption of dyes is presented. Therefore, microspot arrays consisting of different types of organosilane monolayers are exposed to dye solutions. After this immersion, the chips are rinsed in a solvent, resulting in a locally differentiated fluorescence intensity.

A Modified General Regression Neural Network (MGRNN) with new, efficient training algorithms as a robust 'black box'-tool for data analysis.

A Modified General Regression Neural Network (MGRNN) is presented as an easy-to-use 'black box'-tool to feed in available data and obtain a reasonable regression surface. The MGRNN is based on the General Regression Neural Network by D. Specht [Specht, D.