منابع مشابه
Accelerated Profile HMM Searches
Profile hidden Markov models (profile HMMs) and probabilistic inference methods have made important contributions to the theory of sequence database homology search. However, practical use of profile HMM methods has been hindered by the computational expense of existing software implementations. Here I describe an acceleration heuristic for profile HMMs, the "multiple segment Viterbi" (MSV) alg...
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Phylogenetic search is a key tool used in a variety of biological research endeavours. However, this search problem is known to be computationally difficult, due to the astronomically large search space, making the use of heuristic methods necessary. The performance of heuristic methods for finding Maximum Likelihood (ML) trees can be improved by using parsimony as an initial estimator for ML. ...
متن کاملVisualizing profile-profile alignment: pairwise HMM logos
UNLABELLED The availability of advanced profile-profile comparison tools, such as PRC or HHsearch demands sophisticated visualization tools not presently available. We introduce an approach built upon the concept of HMM logos. The method illustrates the similarities of pairs of protein family profiles in an intuitive way. Two HMM logos, one for each profile, are drawn one upon the other. The al...
متن کاملTowards Faster Profile HMM Evaluation
Hidden Markov Models (HMMs) are very popular for a large variety of tasks within the field of pattern recognition. Understanding the input as signals of linear time dependency the use of HMMs becomes reasonable for bioinformatics purposes. Therefore, in the last decade HMMs were introduced to the bioinformatics community for genetic and protein analysis tasks. Serving as probabilistic models of...
متن کاملHHsenser: exhaustive transitive profile search using HMM–HMM comparison
HHsenser is the first server to offer exhaustive intermediate profile searches, which it combines with pairwise comparison of hidden Markov models. Starting from a single protein sequence or a multiple alignment, it can iteratively explore whole superfamilies, producing few or no false positives. The output is a multiple alignment of all detected homologs. HHsenser's sensitivity should make it ...
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ژورنال
عنوان ژورنال: PLoS Computational Biology
سال: 2011
ISSN: 1553-7358
DOI: 10.1371/journal.pcbi.1002195