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    <title>Dror Berel</title>
    <description>professional page</description>
    <link>https://drorberel.github.io</link>
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        <title>Meta Machine Learning aggregator packages in R, The 2nd generation</title>
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          TL;DR mlr was refactored into mlr3. caret was refactored into tidymodels. What are the main differences in terms of software design, and tweaking it for your own needs. R6 vs S3. Which one is less fraigle? Motivation My previous post from mid 2018 described my learning experience with R packages...
        </description>
        <pubDate>Sat, 14 Dec 2019 00:00:00 -0800</pubDate>
        <link>https://drorberel.github.io/2019-12-14-Meta-Machine-Learning-aggregator-packages-in-R-The-2nd-generation/</link>
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      <item>
        <title>Meta analysis of multiple multi-omics data… Oy Vey</title>
        <description>
          
          TL;DR tidy tibbles can contain non-atomic classes. This is a proof of concept demonstration for such implementation with S4 object-oriented classes, for meta-analysis of complex genomic data. Motivation In my previous post I reviewed the evolution of Bioconductor S4 classes for omics data. The most recent extended class is the...
        </description>
        <pubDate>Thu, 25 Apr 2019 00:00:00 -0700</pubDate>
        <link>https://drorberel.github.io/2019-04-25-Meta-analysis-of-multiple-multi-omics-data/</link>
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      <item>
        <title>Bioconductor S4 classes for high-throughput omics data</title>
        <description>
          
          TL;DR These object-oriented contstrained classes saved me so many times, that I can’t imagine my life without them. If it is good enough for the Bioconductor community to keep develop and maintain, there must be something very usefull in it, for other disciplines to learn. Motivation Multi-omics data integration and...
        </description>
        <pubDate>Mon, 15 Apr 2019 00:00:00 -0700</pubDate>
        <link>https://drorberel.github.io/2019-04-15-Bioconductor-S4-classes-for-high-throughput-omics-data/</link>
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      <item>
        <title>Welcome!</title>
        <description>
          
          I am a Computational Biologist at Fred Hutch. My expertise include: S4 classes for assay data, Machine-learning (tuning, benchmarking, resampling, ensemble), meta-analysis and inferential models. Recent projects: Meta analysis of multi-assay data: proof of concept poster: Prototype meta-analysis demonstration for ImmuneSpaceR, using designated S4 objects https://www.bioconductor.org/help/course-materials/2017/BioC2017/DDay/LightningTalk/SessionII/ImmuneSpaceR.pdf Bioc2mlr R package to...
        </description>
        <pubDate>Tue, 29 Jan 2019 00:00:00 -0800</pubDate>
        <link>https://drorberel.github.io/2019-01-29-Welcome/</link>
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