Abstract
We have observed in recent years a growing interest in similarity search on large collections of biological sequences. Contributing to the interest, this paper presents a method for indexing the DNA sequences efficiently based on q-grams to facilitate similarity search in a DNA database and sidestep the need for linear scan of the entire database. Two level index – hash table and c-trees – are proposed based on the q-grams of DNA sequences. The proposed data structures allow the quick detection of sequences within a certain distance to the query sequence. Experimental results show that our method is efficient in detecting similarity regions in a DNA sequence database with high sensitivity.
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Cao, X., Li, S.C., Tung, A.K.H. (2005). Indexing DNA Sequences Using q-Grams. In: Zhou, L., Ooi, B.C., Meng, X. (eds) Database Systems for Advanced Applications. DASFAA 2005. Lecture Notes in Computer Science, vol 3453. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11408079_4
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DOI: https://doi.org/10.1007/11408079_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25334-1
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