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The analysis of chromatin condensation state and transcriptional activity using DNA microarrays

100%

Widłak P. , Fujarewicz K.

tom Vol. 6

IP13--19

The DNA microarray-based technique has been developed to semi-quantitatively measure the in vivo global chromatin condensation state at the resolution of a gene. Chromatin was fractionated due to the differential solubility of histone H1-containing and histone H1-free nucleosomes. A set of genes non-randomly distributed between histone H1-free (uncondensed or open) and histone H1-containing (condensed or closed) chromatin fractions has been identified. The transcript levels have been measured for the same group of genes. The correlation between transcriptional activity and chromatin fraction distribution of particular genes has been established.

Performance of classification methods in a microarray setting: a simulation study

100%

Van Sanden S. , Lin D. , Burzykowski T.

tom Vol. 27, no. 3

15-28

Dudoit et al., Lee et al., and Statnikov et al. investigated the performance of several classification methods applied to real-life microarray data. Due to the availability of only a few datasets, only a limited number of settings could be evaluated. Also, the true classification and the set of truly differentially expressed genes were unknown. In order to overcome these limitations, a simulation study was conducted, by using a linear mixed effects model to simulate microarray data under different scenarios. Several classification methods were compared with respect to their ability to discriminate between two classes of biological samples in various experimental settings.

On the noise attenuation in DNA microarray images

67%

Smolka B. , Szczepański M. , Wojciechowski K. , Plataniotis K. N.

2001

tom Vol. 2, Part. 1

MI19--MI27

In this paper a novel method of noise reduction in color images is presented. The new technique is capable of attenuating both impulsive and Gaussian noise, while preserving and even enhancing sharpness of the image edges. Extensive simulations reveal that the new method outperforms significantly the standard techniques widely used in multivariate signal processing. In this work we apply the new noise reduction method for the enhancement of the images of gene chips. We demonstrate that the new technique is capable of reducing various kinds of noise present in microarray images and that it enables efficient spot location and estimation of the gene expression level due to the smoothing effect and preservation of the spot edges. This paper contains the comparison of the new technique of noise reduction with the standard procedures used for the processing of vector valued images, as well as examples of the efficiency of the new algorithm when applied to typical microarray images.