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Network biology

A compass for stem-cell differentiation

Nature volume 513, pages 498–499 (2014)Cite this article

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The development of CellNet — network-biology software that determines how cell types generated in vitro relate to their naturally occurring counterparts — could improve our ability to produce desirable cells in culture.

Over the past few years, websites such as Facebook and Google have attained an uncanny ability to understand us and to predict our behaviour, even before we have consciously decided what to do. This predictive power is achieved through the systematic application of statistical 'inference algorithms' to the vast numbers of connections and links that users establish when browsing the Internet — making up a 'social graph' that can be exploited to characterize distinct groups of Internet users. It would be wonderful to have such a graph to characterize distinct groups of cells. This could then be used in regenerative medicine to overcome the challenge of coercing stem cells to become the cell type needed for a particular therapy. Writing in Cell, Cahan et al.1 and Morris et al.2 describe a network-biology platform, CellNet, that takes a first step in this direction.

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Figure 1: Improving cellular engineering.

References

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Authors and Affiliations

  1. Franz-Josef Müller is at the Zentrum für Integrative Psychiatrie Kiel, Universitätsklinikum Schleswig-Holstein, 24105 Kiel, Germany.,

    Franz-Josef Müller

  2. Jeanne F. Loring is in the Department of Chemical Physiology, Center for Regenerative Medicine, The Scripps Research Institute, California 92037, USA.,

    Jeanne F. Loring

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  1. Franz-Josef Müller
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  2. Jeanne F. Loring
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Correspondence to Franz-Josef Müller or Jeanne F. Loring.

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Müller, FJ., Loring, J. A compass for stem-cell differentiation. Nature 513, 498–499 (2014). https://doi.org/10.1038/513498a

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