A layered perceptron approach to categorizing cDNA microarray measurements

cDNA Microarray Data Normalization

A Genetic Approach to cDNA Microarray Image Analysis

Microarray image analysis is a significant tool for cDNA microarrays and it is divided in two main stages: Gridding and Spot-Segmentation. Most of the available microarray image analysis tools require human intervention to specify certain landmarks on the grid, or even to precisely locate individual spots. This paper focuses on the development of an original, fully automated gridding and spot-s...

A Data-Adaptive Approach to cDNA Microarray Image Enhancement

A data-adaptive approach for cDNA microarray image enhancement is presented. Through the weighting coefficients adaptively determined from local microarray image statistics, the proposed technique tunes the overall filter’s detail-preserving and noise-attenuating characteristics and uses both the spatial and spectral correlation of the cDNA image during processing. Noise removal is performed by...

A Bayesian approach to the analysis of cDNA microarray data

The recent explosion of interest in microarray technology has resulted in it becoming the preferred methodology for conducting gene expression experiments. Although the ability of an array experiment to simultaneously examine the expression of thousands of genes gives a previously unheard of level of insight to researchers, it also raises a plethora of statistical questions involving both the s...

A novel neural network approach to cDNA microarray image segmentation

Microarray technology has become a great source of information for biologists to understand the workings of DNA which is one of the most complex codes in nature. Microarray images typically contain several thousands of small spots, each of which represents a different gene in the experiment. One of the key steps in extracting information from a microarray image is the segmentation whose aim is ...