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The hit criterion is a key component of heuristic local alignment algorithms. It specifies a class of patterns assumed to witness a potential similarity, and this choice is decisive for the selectivity and sensitivity of the whole method. In this paper, we propose two ways to improve the hit criterion. First, we define the group criterion combining the advantages of the single-seed and double-seed approaches used in existing algorithms. Second, we introduce transition-constrained seeds thatdoi:10.1186/1471-2105-5-149 pmid:15485572 pmcid:PMC526756 fatcat:vkj773vw4jcmdixihpzwwjezxq