Genomics studies routinely depend on similarity searches based on the strategy of finding short seed matches (contiguous k bases) which are then extended. The particular choice of the seed length, k, is determined by the tradeoff between search speed (larger k reduces chance hits) and sensitivity (smaller k finds weaker similarities). A novel idea of using a single deterministic optimized space...

Article history: Received 23 February 2017 Received in revised form 16 May 2017 Accepted 21 May 2017 Available online xxxx

It has been observed that in homology search gapped seeds have better sensitivity than ungapped ones for the same cost (weight). In this paper, we propose a probability leakage model (a dissipative Markov system) to elucidate the mechanism that confers power to spaced seeds. Based on this model, we identify desirable features of gapped search seeds and formulate an extremely efficient procedure...

Optimized spaced seeds improve sensitivity and specificity in local homology search. Several authors have shown that multiple seeds can have better sensitivity and specificity than single seeds. We describe a linear programming (LP)-based algorithm to optimize a set of seeds. Theoretically, our algorithm offers a performance guarantee: the sensitivity of a chosen seed set is at least 70% of wha...

SUMMARY Multiple spaced seeds represent the current state-of-the-art for similarity search in bioinformatics, with applications in various areas such as sequence alignment, read mapping, oligonucleotide design, etc. We present SpEED, a software program that computes highly sensitive multiple spaced seeds. SpEED can be several orders of magnitude faster and computes better seeds than the existin...

Similarity search in biological sequence database is one of the most popular and important bioinformatics tasks. Spaced seeds have been increasingly used to improve the quality and sensitivity of searching, for example, in seeded alignment methods. Finding optimal spaced seeds is a NP-hard problem. In this study we introduce an application of an Ant Colony Optimization (ACO) algorithm to addres...

Homology search finds similar segments between two biological sequences, such as DNA or protein sequences. A significant fraction of the computing power in the world is devoted to finding similarities between biological sequences. The introduction of optimal spaced seeds in [Ma et al., Bioinformatics 18 (2002) 440–445] has increased both the sensitivity and the speed of homology search and it h...

Spaced seeds have been extensively studied in the homology search field. A spaced seed can be regarded as a very special type of hash function on k-mers, where two k-mers have the same hash value if and only if they are identical at the w (w < k) positions designated by the seed. Spaced seeds substantially increased the homology search sensitivity. It is then a natural question to ask whether t...