News & Views

Enabling direct fate conversion with network biology

Current efforts in cellular disease modeling and regenerative medicine are limited by the paucity of cell types that can be generated in the laboratory. A new study introduces a computational framework, Mogrify, that uses network biology to predict combinations of transcription factors necessary for direct conversion between human cell types to ameliorate this issue.

  • Subscribe to Nature Genetics for full access:

    $59

    Subscribe

Additional access options:

Already a subscriber?  Log in  now or  Register  for online access.

References

  1. 1.

    et al. Nat. Genet. 48, 331–335 (2016).

  2. 2.

    et al. Cell 158, 903–915 (2014).

  3. 3.

    et al. Stem Cell Rep. 10.1016/j.stemcr.2015.09.016 (23 October 2015).

  4. 4.

    et al. Nat. Methods 9, 796–804 (2012).

  5. 5.

    FANTOM Consortium and the RIKEN PMI and CLST (DGT). Nature 507, 462–470 (2014).

  6. 6.

    & Proc. Natl. Acad. Sci. USA 111, 9503–9508 (2014).

  7. 7.

    , & Cell 51, 987–1000 (1987).

  8. 8.

    et al. Cell 158, 889–902 (2014).

Download references

Author information

Affiliations

  1. Institute for Cell Engineering and in the Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.

    • Patrick Cahan

Authors

  1. Search for Patrick Cahan in:

Competing interests

The author declares no competing financial interests.

Corresponding author

Correspondence to Patrick Cahan.