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Application of an automatic fuzzy logic based pattern recognition approach for clustering DNA microarray data

机译:基于自动模糊逻辑的模式识别方法在DNA微阵列数据聚类中的应用

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摘要

The past decade has brought about tremendous advances in genetics and molecular biology. Nowadays DNA technology is widely applied in laboratories in order to diagnose accurately and effectively genetic illnesses of patients. The Solas2 is a DNA microarray reader, which is specifically designed for medical laboratory. It bases on the image processing and pattern detection technology to analyze DNA microarrays, extract the feature of genome, and visualize the early-stage diseases. With the help of the DNA microarray reader users can more easily detect and treat those diseases, which could occur in the future. Basing on the fuzzy logic algorithms, a special method was developed for the classification of the extracted DNA features. Because of the irregular distribution of pattern space with classic fuzzy algorithms, the result of pattern detection would not be satisfying. This article will introduce a method which is derived and improved from classic fuzzy logic methods FCM and FML. With this method the recognition of DNA features can be proceeded correctly and effectively.
机译:在过去的十年中,遗传学和分子生物学取得了巨大的进步。如今,DNA技术已广泛应用于实验室,以准确,有效地诊断患者的遗传疾病。 Solas2是一种DNA微阵列读取器,是专门为医学实验室设计的。它基于图像处理和模式检测技术来分析DNA微阵列,提取基因组特征并可视化早期疾病。借助DNA微阵列阅读器,用户可以更轻松地检测和治疗那些将来可能会发生的疾病。基于模糊逻辑算法,开发了一种特殊的方法来对提取的DNA特征进行分类。由于经典模糊算法对模式空间的不规则分布,模式检测的结果将无法令人满意。本文将介绍一种从经典模糊逻辑方法FCM和FML派生和改进的方法。使用这种方法,可以正确有效地进行DNA特征的识别。

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