Efficient seeding techniques for protein similarity search

Abstract : We apply the concept of subset seeds proposed in [1] to similarity search in protein sequences. The main question studied is the design of efficient seed alphabets to construct seeds with optimal sensitivity/selectivity trade-offs. We propose several different design methods and use them to construct several alphabets.We then perform an analysis of seeds built over those alphabet and compare them with the standard Blastp seeding method [2,3], as well as with the family of vector seeds proposed in [4]. While the formalism of subset seed is less expressive (but less costly to implement) than the accumulative principle used in Blastp and vector seeds, our seeds show a similar or even better performance than Blastp on Bernoulli models of proteins compatible with the common BLOSUM62 matrix.
Complete list of metadatas

https://hal.inria.fr/inria-00335564
Contributor : Laurent Noé <>
Submitted on : Wednesday, October 29, 2008 - 8:07:23 PM
Last modification on : Thursday, February 21, 2019 - 10:52:49 AM
Long-term archiving on : Tuesday, June 28, 2011 - 5:34:40 PM

Files

paper.pdf
Files produced by the author(s)

Identifiers

Citation

Mihkail Roytberg, Anna Gambin, Laurent Noé, Slawomir Lasota, Eugenia Furletova, et al.. Efficient seeding techniques for protein similarity search. Proceedings of the 2nd International Conference BIRD, Jul 2008, Vienna, Austria. pp.466-478, ⟨10.1007/978-3-540-70600-7⟩. ⟨inria-00335564⟩

Share

Metrics

Record views

321

Files downloads

268