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Authors: Härtner, Franziska
Andrade, Miguel
Alanis-Lobato, Gregorio
Title: Geometric characterisation of disease modules
Online publication date: 23-Jul-2018
Language: english
Abstract: There is an increasing accumulation of evidence supporting the existence of a hyperbolic geometry underlying the network representation of complex systems. In particular, it has been shown that the latent geometry of the human protein network (hPIN) captures biologically relevant information, leading to a meaningful visual representation of protein-protein interactions and translating challenging systems biology problems into measuring distances between proteins. Moreover, proteins can efficiently communicate with each other, without global knowledge of the hPIN structure, via a greedy routing (GR) process in which hyperbolic distances guide biological signals from source to target proteins. It is thanks to this effective information routing throughout the hPIN that the cell operates, communicates with other cells and reacts to environmental changes. As a result, the malfunction of one or a few members of this intricate system can disturb its dynamics and derive in disease phenotypes. In fact, it is known that the proteins associated with a single disease agglomerate non-randomly in the same region of the hPIN, forming one or several connected components known as the disease module (DM). Here, we present a geometric characterisation of DMs. First, we found that DM positions on the two-dimensional hyperbolic plane reflect their fragmentation and functional heterogeneity, rendering an informative picture of the cellular processes that the disease is affecting. Second, we used a distance-based dissimilarity measure to cluster DMs with shared clinical features. Finally, we took advantage of the GR strategy to study how defective proteins affect the transduction of signals throughout the hPIN.
DDC: 570 Biowissenschaften
570 Life sciences
Institution: Johannes Gutenberg-Universität Mainz
Department: FB 10 Biologie
Place: Mainz
Version: Published version
Publication type: Zeitschriftenaufsatz
License: CC BY
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Journal: Applied network science
Pages or article number: Art. 10
Publisher: Springer International Publishing
Publisher place: Cham
Issue date: 2018
ISSN: 2364-8228
Publisher URL:
Publisher DOI: 10.1007/s41109-018-0066-3
Annotation: Andrade, Miguel veröffentlicht unter: Andrade-Navarro, Miguel A.
Appears in collections:JGU-Publikationen

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