On subset seeds for protein alignment

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 a comparative analysis of seeds built over those alphabets 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 seeds is less expressive (but less costly to implement) than the cumulative 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. Finally, we perform a large-scale benchmarking of our seeds against several main databases of protein alignments. Here again, the results show a comparable or better performance of our seeds vs. BLASTP.
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Submitted on : Wednesday, January 21, 2009 - 12:39:53 AM
Last modification on : Thursday, February 21, 2019 - 10:52:49 AM
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Mikhail Roytberg, Anna Gambin, Laurent Noé, Slawomir Lasota, Eugenia Furletova, et al.. On subset seeds for protein alignment. IEEE/ACM Transactions on Computational Biology and Bioinformatics, Institute of Electrical and Electronics Engineers, 2009, 6 (3), pp.483-494. ⟨10.1109/TCBB.2009.4⟩. ⟨inria-00354773⟩

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