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Artificial Neural Networks pp 229–248Cite as

Leverage Large-Scale Biological Networks to Decipher the Genetic Basis of Human Diseases Using Machine Learning

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Part of the book series: Methods in Molecular Biology ((MIMB,volume 2190))

Abstract

A fundamental question in precision medicine is to quantitatively decode the genetic basis of complex human diseases, which will enable the development of predictive models of disease risks based on personal genome sequences. To account for the complex systems within different cellular contexts, large-scale regulatory networks are critical components to be integrated into the analysis. Based on the fast accumulation of multiomics and disease genetics data, advanced machine learning algorithms and efficient computational tools are becoming the driving force in predicting phenotypes from genotypes, identifying potential causal genetic variants, and revealing disease mechanisms. Here, we review the state-of-the-art methods for this topic and describe a computational pipeline that assembles a series of algorithms together to achieve improved disease genetics prediction through the delineation of regulatory circuitry step by step.

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Acknowledgements

Hao Wang, Jiaxin Yang and Jianrong Wang were supported by NIH R01GM131398. The authors would like to thank iCER at MSU for providing the high-performance computing facilities.

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Author notes

  1. Hao Wang and Jiaxin Yang contributed equally to this work.

Authors and Affiliations

  1. Department of Computational Mathematics, Science and Engineering, Michigan State University, East Lansing, MI, USA

    Hao Wang, Jiaxin Yang & Jianrong Wang

Authors
  1. Hao Wang
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  2. Jiaxin Yang
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  3. Jianrong Wang
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Corresponding author

Correspondence to Jianrong Wang .

Editor information

Editors and Affiliations

  1. Chemistry, Oxford University, Oxford, UK

    Hugh Cartwright

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Wang, H., Yang, J., Wang, J. (2021). Leverage Large-Scale Biological Networks to Decipher the Genetic Basis of Human Diseases Using Machine Learning. In: Cartwright, H. (eds) Artificial Neural Networks. Methods in Molecular Biology, vol 2190. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-0826-5_11

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  • DOI: https://doi.org/10.1007/978-1-0716-0826-5_11

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-0825-8

  • Online ISBN: 978-1-0716-0826-5

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