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Systems Biology of Alzheimer's Disease pp 435–446Cite as

A Computational Network Biology Approach to Uncover Novel Genes Related to Alzheimer’s Disease

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Part of the book series: Methods in Molecular Biology ((MIMB,volume 1303))

Abstract

Recent advances in the fields of genetics and genomics have enabled the identification of numerous Alzheimer’s disease (AD) candidate genes, although for many of them the role in AD pathophysiology has not been uncovered yet. Concomitantly, network biology studies have shown a strong link between protein network connectivity and disease. In this chapter I describe a computational approach that, by combining local and global network analysis strategies, allows the formulation of novel hypotheses on the molecular mechanisms involved in AD and prioritizes candidate genes for further functional studies.

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Acknowledgments

The author acknowledges the “Plan Cancer 2009-2013, Biologie des systèmes” funded by the French government for current support. The author would also like to thank Christine Brun and Daniela Ruffell for critically reading this chapter.

Author information

Authors and Affiliations

  1. Laboratoire TAGC/INSERM UMR_S1090, Parc Scientifique de Luminy, Case 928, 163, Avenue de Luminy, Marseille cedex 9, 13288, France

    Andreas Zanzoni

  2. Aix-Marseille Université, UMR_S1090 TAGC, Marseille, 13288, France

    Andreas Zanzoni

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  1. Andreas Zanzoni
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Correspondence to Andreas Zanzoni .

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Editors and Affiliations

  1. Department of Biochemistry & Cambridge Systems Biology Centre, University of Cambridge, Cambridge, United Kingdom

    Juan I. Castrillo

  2. Department of Biochemistry & Cambridge Systems Biology Centre, University of Cambridge, Cambridge, United Kingdom

    Stephen G. Oliver

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Zanzoni, A. (2016). A Computational Network Biology Approach to Uncover Novel Genes Related to Alzheimer’s Disease. In: Castrillo, J., Oliver, S. (eds) Systems Biology of Alzheimer's Disease. Methods in Molecular Biology, vol 1303. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-2627-5_26

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  • DOI: https://doi.org/10.1007/978-1-4939-2627-5_26

  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-2626-8

  • Online ISBN: 978-1-4939-2627-5

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