Efficient remote homology detection using local structure
نویسندگان
چکیده
منابع مشابه
Efficient remote homology detection using local structure
MOTIVATION The function of an unknown biological sequence can often be accurately inferred if we are able to map this unknown sequence to its corresponding homologous family. At present, discriminative methods such as SVM-Fisher and SVM-pairwise, which combine support vector machine (SVM) and sequence similarity, are recognized as the most accurate methods, with SVM-pairwise being the most accu...
متن کاملEfficient Remote Homology Detection with Secondary Structure
Motivation: The function of an unknown biological sequence can often be accurately inferred if we are able to map this unknown sequence to its corresponding homologous family. Currently, discriminative approach which combines support vector machine and sequence similarity is recognized as the most accurate approach. SVM-Fisher and SVM-pairwise methods are two representatives of this approach, a...
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Remote homology detection refers to the problem of detecting protein homology in cases of low sequence similarity. Existing methods to establish homology relationships via sequence similarity do not work well for these remote homology. In this paper, we present a new method, SVM-HMMSTR, that overcomes the reliance on sequence similarity by taking into consideration the local structure similarit...
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Remote homology detection is a central problem in computational biology. Currently, the most effective tools for addressing this problem are kernel-based discriminative methods employing support vector machines. These methods work by transforming the protein sequences into (a possibly high-dimensional) vector space, called feature space, and deriving a kernel function in the feature space, whic...
متن کاملRemote homolog detection using local sequence-structure correlations.
Remote homology detection refers to the detection of structural homology in proteins when there is little or no sequence similarity. In this article, we present a remote homolog detection method called SVM-HMMSTR that overcomes the reliance on detectable sequence similarity by transforming the sequences into strings of hidden Markov states that represent local folding motif patterns. These stat...
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ژورنال
عنوان ژورنال: Bioinformatics
سال: 2003
ISSN: 1367-4803,1460-2059
DOI: 10.1093/bioinformatics/btg317