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Systems Medicine Applied to Epidemiology

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Principles of Genetics and Molecular Epidemiology

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Abstract

Systems biology can be defined as the analysis of interactions with different biological systems at different complex levels by using different network approaches. Such advances have permeated to different fields, including those of health known as systems medicine. Such a novel tool has been defined as a holistic approach where human health is integrated from different perspectives, from biomedical to environmental and social. Interestingly, nowadays, there are several examples of applications of such technologies to clinics, for instance, whole-genome association studies or digital health applications that have shown to be quite helpful to public health. Therefore, in the present chapter, we resume some of the main tools of systems biology and its applications to health through systems medicine.

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Abbreviations

ODEs:

Ordinary differential equations

GRNs:

Gene regulatory networks

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Acknowledgments

This chapter is part of a registered project at the Instituto Nacional de Geriatría with the number DI-PI-003/2018.

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Authors and Affiliations

  1. Departamento de Ecología Funcional, Instituto de Ecología, UNAM, Mexico City, Mexico

    Juan Carlos Yustis-Rubio

  2. Dirección de Investigación, Instituto Nacional de Geriatría (INGER), Ciudad de México, Mexico

    Juan Carlos Gomez-Verjan

Authors
  1. Juan Carlos Yustis-Rubio
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  2. Juan Carlos Gomez-Verjan
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Corresponding author

Correspondence to Juan Carlos Gomez-Verjan .

Editor information

Editors and Affiliations

  1. Dirección de Investigación Instituto Nacional de Geriatría (INGER), Ciudad de México, Mexico

    Juan Carlos Gomez-Verjan

  2. Dirección de Investigación Instituto Nacional de Geriatría (INGER) Instituto Nacional de Geriatría, Ciudad de México, Mexico

    Nadia Alejandra Rivero-Segura

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Yustis-Rubio, J.C., Gomez-Verjan, J.C. (2022). Systems Medicine Applied to Epidemiology. In: Gomez-Verjan, J.C., Rivero-Segura, N.A. (eds) Principles of Genetics and Molecular Epidemiology. Springer, Cham. https://doi.org/10.1007/978-3-030-89601-0_16

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