Hardware Acceleration of Bioinformatics Sequence Alignment Applications

Biological sequence alignment is an important and challenging task in bioinformatics. Alignment may be defined as an arrangement of two or more DNA or protein sequences to highlight the regions of their similarity. Sequence alignment is used to infer the evolutionary relationship between a set of protein or DNA sequences. An accurate alignment can provide valuable information for experimentation on the newly found sequences. It is indispensable in basic research as well as in practical applications such as pharmaceutical development, drug discovery, disease prevention and criminal forensics. Many algorithms and methods, such as, dot plot, Needleman-Wunsch, Smith-Waterman, FASTA, BLAST, HMMER and ClustalW have been proposed to perform and accelerate sequence alignment activities. However, with the ever increasing volume of data in bioinformatics databases, the time needed for biological sequence alignment is always increasing. The main aim of the research presented in this thesis is to explore and analyze the existing sequence alignment methods and come up with better and optimized solutions.