A DNA based Approach to find Closed Repetitive Gapped Subsequences from a Sequence Database

In bioinformatics, the discovery of transcription factor binding affinities is important. This is done by sequence analysis of micro array data. The determination of continuous and gapped motifs accurately from the given long sequence of data, say genetic data is challenging and requires a detailed study. In this paper, we propose an algorithm that can be used for finding short continuous, short gapped, long continuous, long gapped and negative existence of motifs. We propose a new DNA algorithmic approach which solves the accurate determination of motifs continuous and gapped, parallely with optimum time. Using the proposed algorithm, firstly a modified Position Weight Matrix is generated according to the searched motif pattern, which contains the position of its appearance in the given database, using DNA operations. Then, this Position Weight Matrix is used for searching of continuous and gapped subsequences. The proposed algorithm can be used to search genetic, scientific as well as commercial databases. Implementation results showed the correctness of the algorithm. Finally, the validity of the algorithm is checked and its complexity is analyzed. General Terms Sequence Mining, Pattern Recognition, Data Mining.

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