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Published in:
2008 | OriginalPaper | Chapter
Efficient Seeding Techniques for Protein Similarity Search
Authors : Mikhail Roytberg, Anna Gambin, Laurent Noé, Sławomir Lasota, Eugenia Furletova, Ewa Szczurek, Gregory Kucherov
Published in: Bioinformatics Research and Development
Publisher: Springer Berlin Heidelberg
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We apply the concept of
subset seeds
proposed in ? 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.