19 research outputs found

    XRate: a fast prototyping, training and annotation tool for phylo-grammars

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    BACKGROUND: Recent years have seen the emergence of genome annotation methods based on the phylo-grammar, a probabilistic model combining continuous-time Markov chains and stochastic grammars. Previously, phylo-grammars have required considerable effort to implement, limiting their adoption by computational biologists. RESULTS: We have developed an open source software tool, xrate, for working with reversible, irreversible or parametric substitution models combined with stochastic context-free grammars. xrate efficiently estimates maximum-likelihood parameters and phylogenetic trees using a novel "phylo-EM" algorithm that we describe. The grammar is specified in an external configuration file, allowing users to design new grammars, estimate rate parameters from training data and annotate multiple sequence alignments without the need to recompile code from source. We have used xrate to measure codon substitution rates and predict protein and RNA secondary structures. CONCLUSION: Our results demonstrate that xrate estimates biologically meaningful rates and makes predictions whose accuracy is comparable to that of more specialized tools

    The future for beef

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    Beef is a fast-growing, multi -billion dollar industry today in the United States. And the outlook for tomorrow is most favorable. Beef consumption has increased by 26 pounds per capita during the past 15 years, hitting an all-time high of 90 pounds per capita in 1962. During the same period quality has improved, and now. beef commands even wider consumer acceptance than in the mid-1940\u27s. New technology has lowered production and marketing costs. But even a strong, healthy industry must be sensitive to change--and take advantage of new opportunities for growth and improvement. The beef industry is no exception.https://lib.dr.iastate.edu/card_reports/1016/thumbnail.jp

    Three-dimensional motifs from the SCOR, structural classification of RNA database: extruded strands, base triples, tetraloops and U-turns

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    Release 2.0.1 of the Structural Classification of RNA (SCOR) database, http://scor.lbl.gov, contains a classification of the internal and hairpin loops in a comprehensive collection of 497 NMR and X-ray RNA structures. This report discusses findings of the classification that have not been reported previously. The SCOR database contains multiple examples of a newly described RNA motif, the extruded helical single strand. Internal loop base triples are classified in SCOR according to their three-dimensional context. These internal loop triples contain several examples of a frequently found motif, the minor groove AGC triple. SCOR also presents the predominant and alternate conformations of hairpin loops, as shown in the most well represented tetraloops, with consensus sequences GNRA, UNCG and ANYA. The ubiquity of the GNRA hairpin turn motif is illustrated by its presence in complex internal loops

    SCOR: Structural Classification of RNA, version 2.0

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    SCOR, the Structural Classification of RNA (http://scor.lbl.gov), is a database designed to provide a comprehensive perspective and understanding of RNA motif three-dimensional structure, function, tertiary interactions and their relationships. SCOR 2.0 represents a major expansion and introduces a new classification organization. The new version represents the classification as a Directed Acyclic Graph (DAG), which allows a classification node to have multiple parents, in contrast to the strictly hierarchical classification used in SCOR 1.2. SCOR 2.0 supports three types of query terms in the updated search engine: PDB or NDB identifier, nucleotide sequence and keyword. We also provide parseable XML files for all information. This new release contains 511 RNA entries from the PDB as of 15 May 2003. A total of 5880 secondary structural elements are classified: 2104 hairpin loops and 3776 internal loops. RNA motifs reported in the literature, such as ‘Kink turn’ and ‘GNRA loops’, are now incorporated into the structural classification along with definitions and descriptions
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