Similarity Detection in Biological Sequences using Parameterized Matching and Q-gram

Rama Singh, D. Rai, R. Prasad, Rajeev Singh
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引用次数: 5

Abstract

Whenever characterization of a new DNA sequence takes place then, database search is carried out to find whether homolog’s of gene is present or not. Various evolutions in this field have marked the shift from exact matching to a completely different concept, parameterized matching. Parameterized matching is detected by consistent renaming of text and pattern using bijective mapping. While finding matches between pattern and text, the PBMH-Hash algorithm results in frequent occurrence of false matches with large number of character comparison. This paper presents a new algorithm to detect similarity in biological sequences. The proposed algorithm is based on the concept of Berry-Ravindran algorithm and q-Gram. Analysis shows that our algorithm outperforms existing PBMH-Hash algorithm.
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基于参数化匹配和Q-gram的生物序列相似性检测
每当对新的DNA序列进行鉴定时,都要进行数据库检索,以确定是否存在同源基因。该领域的各种发展标志着从精确匹配到一个完全不同的概念,参数化匹配的转变。通过双目标映射对文本和模式进行一致的重命名来检测参数化匹配。pbh - hash算法在查找模式和文本之间的匹配时,由于需要进行大量的字符比较,导致频繁出现错误匹配。提出了一种新的生物序列相似性检测算法。该算法基于Berry-Ravindran算法和q-Gram的概念。分析表明,该算法优于现有的pbh - hash算法。
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