2009International Journal on Information Sciences and ComputingOpen access

A NEW ALGORITHM FOR GLOBAL ALIGNMENT IN DNA SEQUENCING

V. Anitha, B. Poorna

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Abstract

Alignment is the most basic component of biological sequence manipulation and has diverse applications in sequence assembly, sequence annotation, structural and functional predictions for genes and proteins, phylogeny and evolutionary analysis. Classical methods like Needleman Wunsch ( for global alignment) in 1970 and Smith-Waterman (for local alignment) in 1981 suffer from the drawback that it involves a large number of computational steps and has a statically allocate a large section of memory for computer implementation. This paper suggests an alternate method to obtain global alignment between two sequences using logic gates and compare the performance of our algorithm with that of the classical method.

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Alignment is the most basic component of biological sequence manipulation and has diverse applications in sequence assembly, sequence annotation, structural and functional predictions for genes and proteins, phylogeny and evolutionary analysis. Classical methods like Needleman Wunsch ( for global alignment) in 1970 and Smith-Waterman (for local alignment) in 1981 suffer from the drawback that it involves a large number of computational steps and has a statically allocate a large section of memory for computer implementation. This paper suggests an alternate method to obtain global alignment between two sequences using logic gates and compare the performance of our algorithm with that of the classical method.

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Available abstract

Alignment is the most basic component of biological sequence manipulation and has diverse applications in sequence assembly, sequence annotation, structural and functional predictions for genes and proteins, phylogeny and evolutionary analysis. Classical methods like Needleman Wunsch ( for global alignment) in 1970 and Smith-Waterman (for local alignment) in 1981 suffer from the drawback that it involves a large number of computational steps and has a statically allocate a large section of memory for computer implementation. This paper suggests an alternate method to obtain global alignment between two sequences using logic gates and compare the performance of our algorithm with that of the classical method.

Key concepts: DNA sequencing, Computer science, Algorithm, Computational biology, DNA, Biology, Genetics

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