Skip to main content

Thank you for visiting You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

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.

This is a preview of subscription content, access via your institution

Access options

Rent or buy this article

Get just this article for as long as you need it


Prices may be subject to local taxes which are calculated during checkout

Figure 1: The two major barriers to achieving cell fate engineering.


  1. Rackham, O.J.L. et al. Nat. Genet. 48, 331–335 (2016).

    Article  CAS  Google Scholar 

  2. Cahan, P. et al. Cell 158, 903–915 (2014).

    Article  CAS  Google Scholar 

  3. D'Alessio, A.C. et al. Stem Cell Rep. 10.1016/j.stemcr.2015.09.016 (23 October 2015).

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

    Article  CAS  Google Scholar 

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

  6. Li, V.C. & Kirschner, M.W. Proc. Natl. Acad. Sci. USA 111, 9503–9508 (2014).

    Article  CAS  Google Scholar 

  7. Davis, R.L., Weintraub, H. & Lassar, A.B. Cell 51, 987–1000 (1987).

    Article  CAS  Google Scholar 

  8. Morris, S.A. et al. Cell 158, 889–902 (2014).

    Article  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations


Corresponding author

Correspondence to Patrick Cahan.

Ethics declarations

Competing interests

The author declares no competing financial interests.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Cahan, P. Enabling direct fate conversion with network biology. Nat Genet 48, 226–227 (2016).

Download citation

  • Published:

  • Issue Date:

  • DOI:


Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing