Jason H. Moore

Jason H. Moore Jason H. Moore is a translational bioinformatics scientist, biomedical informatician, and human geneticist, the Edward Rose Professor of Informatics and Director of the Institute for Biomedical Informatics at the Perelman School of Medicine at the University of Pennsylvania, where he is also Senior Associate Dean for Informatics and Director of the Division of Informatics in the Department of Biostatistics, Epidemiology, and Informatics. Provided by Wikipedia
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  1. 1
    Ten important roles for academic leaders in data science

    Ten important roles for academic leaders in data science by Jason H. Moore

    Published 2020-10-01
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  2. 2
    Empowering the data science scientist

    Empowering the data science scientist by Jason H. Moore

    Published 2021-01-01
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  3. 3
    A comparison of methods for interpreting random forest models of genetic association in the presence of non-additive interactions

    A comparison of methods for interpreting random forest models of genetic association in the presence of non-additive interactions by Alena Orlenko, Jason H. Moore

    Published 2021-01-01
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  4. 4
    Artificial intelligence: more human with human

    Artificial intelligence: more human with human by Moshe Sipper, Jason H. Moore

    Published 2017-12-01
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  5. 5
    Eleven quick tips for architecting biomedical informatics workflows with cloud computing.

    Eleven quick tips for architecting biomedical informatics workflows with cloud computing. by Brian S Cole, Jason H Moore

    Published 2018-03-01
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  6. 6
    Chapter 11: Genome-wide association studies.

    Chapter 11: Genome-wide association studies. by William S Bush, Jason H Moore

    Published 2012-01-01
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  7. 7
    STAR_outliers: a python package that separates univariate outliers from non-normal distributions

    STAR_outliers: a python package that separates univariate outliers from non-normal distributions by John T. Gregg, Jason H. Moore

    Published 2023-09-01
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  8. 8
    Conservation machine learning: a case study of random forests

    Conservation machine learning: a case study of random forests by Moshe Sipper, Jason H. Moore

    Published 2021-02-01
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  9. 9
    Conservation machine learning

    Conservation machine learning by Moshe Sipper, Jason H. Moore

    Published 2020-08-01
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  10. 10
    Improving machine learning reproducibility in genetic association studies with proportional instance cross validation (PICV)

    Improving machine learning reproducibility in genetic association studies with proportional instance cross validation (PICV) by Elizabeth R. Piette, Jason H. Moore

    Published 2018-04-01
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  11. 11
    Genetics and precision health: the ecological fallacy and artificial intelligence solutions

    Genetics and precision health: the ecological fallacy and artificial intelligence solutions by Scott M. Williams, Jason H. Moore

    Published 2023-03-01
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  12. 12
    Identification of epistatic interactions between the human RNA demethylases FTO and ALKBH5 with gene set enrichment analysis informed by differential methylation

    Identification of epistatic interactions between the human RNA demethylases FTO and ALKBH5 with gene set enrichment analysis informed by differential methylation by Elizabeth R. Piette, Jason H. Moore

    Published 2018-09-01
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  13. 13
    Knowledge graph aids comprehensive explanation of drug and chemical toxicity

    Knowledge graph aids comprehensive explanation of drug and chemical toxicity by Yun Hao, Joseph D. Romano, Jason H. Moore

    Published 2023-08-01
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  14. 14
    To know the objective is not (necessarily) to know the objective function

    To know the objective is not (necessarily) to know the objective function by Moshe Sipper, Ryan J. Urbanowicz, Jason H. Moore

    Published 2018-10-01
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  15. 15
    Analysis validation has been neglected in the Age of Reproducibility.

    Analysis validation has been neglected in the Age of Reproducibility. by Kathleen E Lotterhos, Jason H Moore, Ann E Stapleton

    Published 2018-12-01
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  16. 16
    Novel digital approaches to the assessment of problematic opioid use

    Novel digital approaches to the assessment of problematic opioid use by Philip J. Freda, Henry R. Kranzler, Jason H. Moore

    Published 2022-07-01
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  17. 17
    Correction to: Investigating the parameter space of evolutionary algorithms

    Correction to: Investigating the parameter space of evolutionary algorithms by Moshe Sipper, Weixuan Fu, Karuna Ahuja, Jason H. Moore

    Published 2019-11-01
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  18. 18
    Phenotypic robustness and the assortativity signature of human transcription factor networks.

    Phenotypic robustness and the assortativity signature of human transcription factor networks. by Dov A Pechenick, Joshua L Payne, Jason H Moore

    Published 2014-08-01
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  19. 19
    Investigating the parameter space of evolutionary algorithms

    Investigating the parameter space of evolutionary algorithms by Moshe Sipper, Weixuan Fu, Karuna Ahuja, Jason H. Moore

    Published 2018-02-01
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  20. 20
    Multi-class computational evolution: development, benchmark evaluation and application to RNA-Seq biomarker discovery

    Multi-class computational evolution: development, benchmark evaluation and application to RNA-Seq biomarker discovery by Nathaniel M. Crabtree, Jason H. Moore, John F. Bowyer, Nysia I. George

    Published 2017-04-01
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