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Coupling Large-Scale Omics Data for Deciphering Systems Complexity

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Systems Biology

Part of the book series: RNA Technologies ((RNATECHN))

Abstract

Recent development in high-throughput experiments has provided great amount of data that is being used in translational personalized medicine. Data available in public databases is increasing exponentially as a result of the progress in omics technologies including genomics, epigenomics, transcriptomics, proteomics, and metabolomics. Advancements in computing power and machine intelligence are affecting large-scale data analysis and integration. Two types of data integration are often considered: horizontal and vertical meta-analysis. The former integrates multiple studies of the same type, while the latter integrates data at different biological levels. This integrative approach provides a better understanding of systems complexity as a result of the global view that it offers from a biological point of view. This chapter describes the different types of omics analysis and discusses the methods of integrating multi-omics data using a case study.

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Author notes

  1. Ali Nehme and Zahraa Awada contributed equally and are hence considered co-first authors.

Authors and Affiliations

  1. Université François Rabelais, CNRS UMR 7292, LNOx Team, Tours, France

    Ali Nehme & Frédéric Mazurier

  2. ER045, PRASE, DSST, Lebanese University, Beirut, Lebanon

    Ali Nehme, Zahraa Awada & Kazem Zibara

  3. Department of Biochemistry and Molecular Genetics, Faculty of Medicine, American University of Beirut, Beirut, Lebanon

    Firas Kobeissy

  4. Biology Department, Faculty of Sciences-I, Lebanese University, Beirut, Lebanon

    Kazem Zibara

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  1. Ali Nehme
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  2. Zahraa Awada
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  3. Firas Kobeissy
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  4. Frédéric Mazurier
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Correspondence to Kazem Zibara .

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Editors and Affiliations

  1. Max Delbrück Center for Molecular Medicine, Berlin Institute for Medical Systems Biology, Berlin-Buch, Berlin, Germany

    Nikolaus Rajewsky

  2. Nanobiomedical Center, Adam Mickiewicz University, Poznań, Poland

    Stefan Jurga

  3. Polish Academy of Sciences, Institute of Bioorganic Chemistry, Poznań, Poland

    Jan Barciszewski

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Nehme, A., Awada, Z., Kobeissy, F., Mazurier, F., Zibara, K. (2018). Coupling Large-Scale Omics Data for Deciphering Systems Complexity. In: Rajewsky, N., Jurga, S., Barciszewski, J. (eds) Systems Biology. RNA Technologies. Springer, Cham. https://doi.org/10.1007/978-3-319-92967-5_8

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