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Systems biology as an emerging paradigm in transfusion medicine

Systems biology as an emerging paradigm in transfusion medicine

Title: Systems biology as an emerging paradigm in transfusion medicine
Author: Yurkovich, James   orcid.org/0000-0002-9403-509X
Bordbar, Aarash
Sigurjonsson, Olafur   orcid.org/0000-0002-4968-842X
Palsson, Bernhard O.
Date: 2018-03-07
Language: English
Scope: 31
University/Institute: Háskólinn í Reykjavík
Reykjavik University
School: Tækni- og verkfræðideild (HR)
School of Science and Engineering (RU)
Series: BMC Systems Biology;12(1)
ISSN: 1752-0509
DOI: 10.1186/s12918-018-0558-x
Subject: Modelling and Simulation; Applied Mathematics; Molecular Biology; Structural Biology; Computer Science Applications; Systems biology; Red blood cell; Transfusion medicine; Metabolism; Storage lesion; Líkanagerð; Stærðfræði; Sameindalíffræði; Forrit; Blóðkorn; Blóðgjöf; Lyf; Efnaskipti
URI: https://hdl.handle.net/20.500.11815/1312

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Yurkovich, J. T., Bordbar, A., Sigurjónsson, Ó. E., & Palsson, B. O. (2018). Systems biology as an emerging paradigm in transfusion medicine. BMC Systems Biology, 12(1), 31. https://doi.org/10.1186/s12918-018-0558-x


Blood transfusions are an important part of modern medicine, delivering approximately 85 million blood units to patients annually. Recently, the field of transfusion medicine has started to benefit from the “omic” data revolution and corresponding systems biology analytics. The red blood cell is the simplest human cell, making it an accessible starting point for the application of systems biology approaches. In this review, we discuss how the use of systems biology has led to significant contributions in transfusion medicine, including the identification of three distinct metabolic states that define the baseline decay process of red blood cells during storage. We then describe how a series of perturbations to the standard storage conditions characterized the underlying metabolic phenotypes. Finally, we show how the analysis of high-dimensional data led to the identification of predictive biomarkers. The transfusion medicine community is in the early stages of a paradigm shift, moving away from the measurement of a handful of chosen variables to embracing systems biology and a cell-scale point of view.


© The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated

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