Discriminative modelling of context-specific amino acid substitution probabilities
نویسندگان
چکیده
منابع مشابه
Discriminative modelling of context-specific amino acid substitution probabilities
MOTIVATION Protein sequence searching and alignment are fundamental tools of modern biology. Alignments are assessed using their similarity scores, essentially the sum of substitution matrix scores over all pairs of aligned amino acids. We previously proposed a generative probabilistic method that yields scores that take the sequence context around each aligned residue into account. This method...
متن کاملDiscriminative modeling of context-specific amino acid substitution probabilities
2 THE DISCRIMINATIVE MODEL SPACE CONTAINS THE GENERATIVE MODEL SPACE In the following we will show that the generative model with any set of parameters is equivalent to the discriminative model with an appropriately chosen set of parameters. In other words, the discriminative model with these particular parameters predicts the same context-specific substitution probabilities P (a|Ci) as the gen...
متن کاملAmino Acid Substitution Scores
GNPKVKAH Here we discuss standard ways of assigning a score to each amino acid pair, i.e., to each possible column of a gap-free pairwise protein alignment. Examples of such scoring matrices include the PAM30, PAM70, BLOSUM80, BLOSUM62 and BLOSUM45 matrices that are available on NCBI’s blastp server. Such scores are appropriate for comparing two sequences about which we have no other informatio...
متن کاملAmino Acid Substitution Scores
GNPKVKAH Here we discuss standard ways of assigning a score to each amino acid pair, i.e., to each possible column of a gap-free pairwise protein alignment. Examples of such scoring matrices include the PAM30, PAM70, BLOSUM80, BLOSUM62 and BLOSUM45 matrices that are available on NCBI’s blastp server. Such scores are appropriate for comparing two sequences about which we have no other informatio...
متن کاملAmino acid substitution matrices.
The BLOSUM (BLOck SUbstitution Matrices) matrices were derived by Steven and Jorja Henikoff in 1992 1. They were based on a much larger data set than the PAM matrices, and used conserved local alignments or “blocks,” rather than global alignments of very closely related sequences. In order to account for different degrees of sequence divergence, the Henikoffs used clustering rather than an expl...
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ژورنال
عنوان ژورنال: Bioinformatics
سال: 2012
ISSN: 1460-2059,1367-4803
DOI: 10.1093/bioinformatics/bts622