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The Power of Machine Learning in the Biological Context

Author

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  • Johannes Stübinger

    (Department of Statistics and Econometrics, University of Erlangen-Nürnberg, Germany)

Abstract

In the recent past, both the rapid growth of big data and the exponential increase in computing power have enabled the use of Machine Learning. In biology, too, this type of artificial intelligence finds very great accusation, as it opens new fields of research. Therefore, this paper provides a comprehensive overview of Machine Learning in biology by consolidating and organizing the extensive literature available in this field of research.

Suggested Citation

  • Johannes Stübinger, 2019. "The Power of Machine Learning in the Biological Context," Biostatistics and Biometrics Open Access Journal, Juniper Publishers Inc., vol. 9(4), pages 102-104, June.
    • Handle: RePEc:adp:jbboaj:v:9:y:2019:i:4:p:102-104
    DOI: 10.19080/BBOAJ.2019.09.555770
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    References listed on IDEAS

    as
    1. Julian Knoll & Johannes Stübinger & Michael Grottke, 2019. "Exploiting social media with higher-order Factorization Machines: statistical arbitrage on high-frequency data of the S&P 500," Quantitative Finance, Taylor & Francis Journals, vol. 19(4), pages 571-585, April.
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