8 research outputs found

    On analysing supply and demand in labor markets: Framework, model and system

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    National Research Foundation (NRF) Singapor

    The Phyre2 web portal for protein modeling, prediction and analysis

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    Phyre2 is a suite of tools available on the web to predict and analyze protein structure, function and mutations. The focus of Phyre2 is to provide biologists with a simple and intuitive interface to state-of-the-art protein bioinformatics tools. Phyre2 replaces Phyre, the original version of the server for which we previously published a paper in Nature Protocols. In this updated protocol, we describe Phyre2, which uses advanced remote homology detection methods to build 3D models, predict ligand binding sites and analyze the effect of amino acid variants (e.g., nonsynonymous SNPs (nsSNPs)) for a user's protein sequence. Users are guided through results by a simple interface at a level of detail they determine. This protocol will guide users from submitting a protein sequence to interpreting the secondary and tertiary structure of their models, their domain composition and model quality. A range of additional available tools is described to find a protein structure in a genome, to submit large number of sequences at once and to automatically run weekly searches for proteins that are difficult to model. The server is available at http://www.sbg.bio.ic.ac.uk/phyre2. A typical structure prediction will be returned between 30 min and 2 h after submission

    Simulations of trading markets

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    Bibliography: p. 78-80

    Accurate somatic variant detection using weakly supervised deep learning

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    Deep learning could be applied to the challenge of somatic variant calling in cancer by making use of large-scale genomic data. Here, the authors develop VarNet, a weakly supervised deep learning model for somatic variant calling in cancer with robust performance across multiple cancer genomics datasets
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