Homology Search Methods
نویسندگان
چکیده
Homology search methods have advanced substantially in recent years. Beginning with the elegant Needleman-Wunsch and Smith-Waterman dynamic programming techiques of the 1970s, algorithms have been developed that were appropriate for the data sets and computer systems of their times. As data sets grew, faster but less sensitive heuristic algorithms, such as FASTA and BLAST, became a dominant force in the late 1980s and 1990s. As datasets have grown still larger in the post-genome era, new technologies have appeared to address these new problems. For example, the optimal spaced seeds of PatternHunter increase speed and sensitivity. Using these ideas, we can achieve BLAST-level speed and sensitivity approaching that of slow algorithms like the Smith-Waterman, bringing us back to a full circle. We wish to take you with us on this round trip, with some detours along the way so as to study both global and local alignment. We present methods for general purpose homology that are widely adopted, not individual programs.
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