A Review on Gridding Techniques of Microarray Images

Karthik Sa, Manjunath Ss, Prakyath Dp, Prashanth S, Vamshi Krishna, Siddartha
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引用次数: 1

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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微阵列图像网格技术综述
微阵列技术是分析生物体内DNA表达的重要工具和有力技术,可用于大规模基因序列和基因表达分析。微阵列技术允许在单个杂交实验中大规模并行,高通量分析基因表达。微阵列图像的处理为进一步分析提取的微阵列数据提供了输入。这项工作涉及到用于网格化图像的方法的基本原则。网格化已经成为微阵列图像分析中的一个重要目标。本文采用网格对齐、子网格检测、贝叶斯模型、爬坡法、遗传算法和最优多级阈值分割等方法对图像进行网格化处理。本文重点介绍了目前广泛应用于图像网格化的各种方法。
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