Laurent Noé1, Gregory Kucherov
1LORIA/INRIA-Lorraine, Villers-lès-Nancy France. Laurent.Noe@loria.fr
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This study enhances heuristic local alignment algorithms by introducing a novel group criterion and transition-constrained seeds. These improvements boost similarity search sensitivity without increasing computational time.
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