基于正则表达式的基因表达数据模式匹配识别异常基因组

2017 Second International Conference on Recent Trends and Challenges in Computational Models (ICRTCCM) Pub Date : 2017-02-01 DOI:10.1109/ICRTCCM.2017.71

L. Sharmila, U. Sakthi, A. Geethanjali, S. Sagadevan

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引用次数: 3

摘要

本文的主要思想是从基因表达数据集中检测和提取输入模式。人类的行为和健康状况可以通过他们的基因组数据准确地识别和分类。本文的目的是寻找和识别基因表达数据中的异常模式可用性。为此，提出了一种基于正则表达式的模式匹配(REPM)方法，用于检测、识别和计数给定数据集中异常模式的出现次数。该方法在MATLAB软件中进行了实验，结果验证了REPM方法的有效性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Regular Expression Based Pattern Matching for Gene Expression Data to Identify the Abnormality Gnome

The main idea of this paper is to detect and extract an input pattern from a gene expression dataset. Human behavior and health conditions can be identified and classified through their genomic data in accurate manner. In this paper it is motivated to search and identify the abnormal pattern availability in a gene expression data. To do this a Regular Expression based Pattern Matching (REPM) method is proposed for detecting, identifying and counting number of abnormal pattern occurrences in a given dataset. This approach is experimented in MATLAB software the results verified to check the efficiency of REPM method.

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来源期刊

2017 Second International Conference on Recent Trends and Challenges in Computational Models (ICRTCCM)

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