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In bioinformatics, a spaced seed is a pattern of relevant and irrelevant positions in a biosequence and a method of approximate string matching that allows for substitutions. They are a straightforward modification to the earliest heuristic -based alignment efforts that allow for minor differences between the sequences of interest.
Feb 28, 2012 · Spaced seeds. A spaced seed is any string containing 1's and *'s. Since having a * at one end of a seed is not useful, we assume that all seed start and end with a 1. For a seed s, the weight w of s is the number of 1's and the length ℓ is the number of all letters. The i th letter of s is denoted s [ i ].
- Silvana Ilie
- silvana@ryerson.ca
- 2012
Oct 24, 2023 · For example, one popular spaced seed is 111010010100110111 introduced in . Elements 1 mean that we take into account possible differences, while in the case of elements 0 , we ignore them. The total number of 1 -elements is called the weight of a seed, and the total number of all elements of a seed is the length .
Nov 30, 2018 · Definition 1. (Spaced seed.) A spaced-seed S (or just a seed) is a binary string of length k, where the symbol ‘ 1 ’ requires a match in that position, while a symbol ‘ 0 ’ allows for “don’t care”. A spaced seed is characterized by its length k and by its weight W < k, which is the number of 1s in the string.
- Samuele Girotto, Matteo Comin, Cinzia Pizzi
- 2018
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Jul 8, 2020 · A spaced seed is a template of zeros and ones, where ones indicate required match positions on a sequence, and zeros indicate wild-card positions where a match or no-match is immaterial. The number of ones in a spaced seed is defined to be its weight.
Feb 28, 2012 · Spaced seeds are much more sensitive than the consecutive seed of BLAST and using several seeds represents the current state of the art in approximate search for biological sequences. The most important aspect is computing highly sensitive seeds.
Jun 10, 2022 · The sensitivity of spaced seed patterns is related to the number of overlapping hits . Hits of contiguous seed patterns (M1) tend to cluster, while hits of seed patterns with low self-overlap are more evenly distributed and thus more sensitive . Thus, one needs to use optimized spaced seed patterns to get the best results.
