Abstract
Microarray is an important tool and powerful technique that is used to analyze the expression of DNA in organisms for large scale gene sequences and gene expressions. Microarray technology allows massively parallel, high throughput profiling of gene expression in a single hybridization experiment. Processing of microarray images provides the input for further analysis of the extracted microarray data. This work deals on the basic principles on the methods used to grid an image. Gridding has become a prominent objective in microarray image analysis. To grid an image various methods such as grid alignment, sub grid detection, Bayesian Model, hill climbing approach, genetic algorithm and optimal multilevel thresholding has been taken for this study. This paper focuses on the various methods that are widely used to grid the image.
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