منابع مشابه
Motif-based fold assignment.
Conventional fold recognition techniques rely mainly on the analysis of the entire sequence of a protein. We present an MBA method to improve performance of any conventional sequence-based fold assignment. The method uses sequence motifs, such as those defined in the Prosite database, and the SwissProt annotation of the fold library. When combined with a simple SDP method, the coverage of MBA i...
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We study the problem of allocating objects by means of probabilistic mechanisms. Each agent has strict preferences over objects and ex post receives exactly one object. A standard approach in the literature is to extend agents' preferences over objects to preferences over lotteries de ned on those objects, using the rst-order stochastic dominance criterion, or the sd-extension. In a departure f...
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Because of the relatively large gap of knowledge between number of protein sequences and protein structures, the ability to construct a computational model predicting structure from sequence information has become an important area of research. The knowledge of a protein's structure is crucial in understanding its biological role. In this work, we present a support vector machine based method f...
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Motif discovery is a crucial part of regulatory network identification, and therefore widely studied in the literature. Motif discovery programs search for statistically significant, well-conserved and over-represented patterns in given promoter sequences. When gene expression data is available, there are mainly three paradigms for motif discovery; cluster-first, regression, and joint probabili...
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This paper describes an approach to data-driven discovery of sequence motif-based models in the form of decision trees for assigning protein sequences to functional families. Unlike approaches that try to classify protein sequences based on presence of a single motif, this method is able to capture regularities that can be described in terms of presence or absence of arbitrary combinations of m...
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ژورنال
عنوان ژورنال: Protein Science
سال: 2008
ISSN: 0961-8368
DOI: 10.1110/ps.14401