A Study of Choosing Efficient Discriminative Seeds for Oligonucleotide Design

Oligonucleotide design is known as a time-consuming work in Bioinformatics. In order to accelerate the oligonucleotide design process, one of the most widely used approaches is the prescreening unreliable regions using hashing(or seeding) method represented by BLAST. Since the seeding is originally proposed to increase the sensitivity for local alignment, the specificity should be considered as well as the sensitivity for the oligonucleotide design problem. However, a measure of evaluating the seeds regarding how adequate and efficient they are in the oligo design is not yet proposed. we propose a novel measure of evaluating the seeding algorithms based on the discriminability and the efficiency. By the proposed measure, five well-known seeding algorithms are examined. The spaced seed is recorded as the best efficient discriminative seed for oligo design.