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An Evolutionary Approach for Correcting Random Amplified Polymorphism DNA Images

机译:一种校正随机扩增多态性DNA图像的进化方法

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Random amplified polymorphism DNA (RAPD) analysis is a widely used technique in studying genetic relationships between individuals, in which processing the underlying images is a quite difficult problem, affected by various factors. Among these factors, noise and distortion affect the quality of images, and subsequently, accuracy in interpreting the data. We propose a method for processing RAPD images that allows to improve their quality and thereof, augmenting biological conclusions. This work presents a twofold objective that attacks the problem by considering two noise sources: band distortion and lane misalignment in the images. Genetic algorithms have shown good results in treating difficult problems, and the results obtained by using them in this particular problem support these directions for future work.
机译:随机扩增的多态性DNA(RAPD)分析是一种广泛使用的技术,用于研究个体之间的遗传关系,其中处理底层图像是受各种因素影响的相当困难的问题。在这些因素中,噪声和失真影响图像的质量,随后,准确地解释数据。我们提出了一种处理RAPD图像的方法,该图像允许提高其质量及其质量,增强生物学结论。这项工作介绍了一个双重目标,通过考虑两个噪声来源来攻击问题:频带失真和图像中的车道未对准。遗传算法表明了治疗困难问题的良好结果,并且通过在该特定问题中使用它们获得的结果支持这些方向以供将来的工作。

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