title: On subset seeds for protein alignment.
abstract: We apply the concept of subset seeds 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, as well as with the family of vector seeds. 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 versus Blastp.
authors: Institute of Mathematical Problems in Biology, Pushchino, Moscow Region 142290, Russia. mroytberg@mail.ru
authors: Mikhail
authors: M
authors: Roytberg
authors: Anna
authors: A
authors: Gambin
authors: Laurent
authors: L
authors: Noé
authors: Slawomir
authors: S
authors: Lasota
authors: Eugenia
authors: E
authors: Furletova
authors: Ewa
authors: E
authors: Szczurek
authors: Gregory
authors: G
authors: Kucherov
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D000596:Amino Acids; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods*; D008954:Models, Biological; D011506:Proteins / Q000737:chemistry* / Q000235:genetics*; D012372:ROC Curve; D016415:Sequence Alignment; D009626:Terminology as Topic
chemical_list: D000596:Amino Acids; D011506:Proteins