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Article . 2019
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Annual Review of Pathology Mechanisms of Disease
Article . 2019 . Peer-reviewed
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Apollo
Article . 2018
Data sources: Datacite
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Modeling Disease with Human Inducible Pluripotent Stem Cells

Authors: Grandy, Rodrigo; Tomaz, Rute A; Vallier, Ludovic;

Modeling Disease with Human Inducible Pluripotent Stem Cells

Abstract

Understanding the physiopathology of disease remains an essential step in developing novel therapeutics. Although animal models have certainly contributed to advancing this enterprise, their limitation in modeling all the aspects of complex human disorders is one of the major challenges faced by the biomedical research field. Human induced pluripotent stem cells (hiPSCs) derived from patients represent a great opportunity to overcome this deficiency because these cells cover the genetic diversity needed to fully model human diseases. Here, we provide an overview of the history of hiPSC technology and discuss common challenges and approaches that we and others have faced when using hiPSCs to model disease. Our emphasis is on liver disease, and consequently, we review the progress made using this technology to produce functional liver cells in vitro and how these systems are being used to recapitulate a diversity of developmental, metabolic, genetic, and infectious liver disorders.

Related Organizations
Keywords

hiPSCs, disease modeling, Induced Pluripotent Stem Cells, Hepatocytes, reprogramming, Humans, Cell Differentiation, differentiation, liver, Models, Biological

  • BIP!
    Impact byBIP!
    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    17
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
17
Top 10%
Average
Top 10%
Green
bronze