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    Current state of and future opportunities for prediction in microbiome research: Report from the mid-atlantic microbiome meet-up in Baltimore on 9 january 2019

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    Author
    Sakowski, E.
    Mongodin, E.F.
    Regan, M.J.
    Date
    2019
    Journal
    mSystems
    Publisher
    American Society for Microbiology
    Type
    Article
    
    Metadata
    Show full item record
    See at
    https://doi.org/10.1128/mSystems.00392-19
    Abstract
    Accurate predictions across multiple fields of microbiome research have far-reaching benefits to society, but there are few widely accepted quantitative tools to make accurate predictions about microbial communities and their functions. More discussion is needed about the current state of microbiome analysis and the tools required to overcome the hurdles preventing development and implementation of predictive analyses. We summarize the ideas generated by participants of the Mid-Atlantic Microbiome Meet-up in January 2019. While it was clear from the presentations that most fields have advanced beyond simple associative and descriptive analyses, most fields lack essential elements needed for the development and application of accurate microbiome predictions. Participants stressed the need for standardization, reproducibility, and accessibility of quantitative tools as key to advancing predictions in microbiome analysis. We highlight hurdles that participants identified and propose directions for future efforts that will advance the use of prediction in microbiome research. Copyright 2019 Sakowski et al.
    Keyword
    Bioinformatics
    Conceptual Models
    Machine learning
    Metagenomics
    Microbiome
    Prediction
    Quantitative models
    Identifier to cite or link to this item
    https://www.scopus.com/inward/record.uri?eid=2-s2.0-85075718442&doi=10.1128%2fmSystems.00392-19&partnerID=40&md5=24b8ffcc32aea6e0502e409eb73d43d8; http://hdl.handle.net/10713/11513
    ae974a485f413a2113503eed53cd6c53
    10.1128/mSystems.00392-19
    Scopus Count
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    UMB Open Access Articles 2019

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