Molecular, phenotypic, and sample-associated data to describe pluripotent stem cell lines and derivatives

Daily, K., Ho Sui, S. J., Schriml, L. M. et al. (20 more authors) (2017) Molecular, phenotypic, and sample-associated data to describe pluripotent stem cell lines and derivatives. Scientific Data, 4. 170030. ISSN 2052-4463

Abstract

Metadata

Authors/Creators:
  • Daily, K.
  • Ho Sui, S. J.
  • Schriml, L. M.
  • Dexheimer, P. J.
  • Salomonis, N.
  • Schroll, R.
  • Bush, S.
  • Keddache, M.
  • Mayhew, C.
  • Lotia, S.
  • Perumal, T. M.
  • Dang, K.
  • Pantano, L.
  • Pico, A. R.
  • Grassman, E.
  • Nordling, D.
  • Hide, W. ORCID logo https://orcid.org/0000-0002-8621-3271
  • Hatzopoulos, A. K.
  • Malik, P.
  • Cancelas, J. A.
  • Lutzko, C.
  • Aronow, B. J.
  • Omberg, L.
Copyright, Publisher and Additional Information: © The Author(s) 2017. This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0 Metadata associated with this Data Descriptor is available at http://www.nature.com/sdata/ and is released under the CC0 waiver to maximize reuse.
Dates:
  • Published: 28 March 2017
  • Accepted: 9 December 2016
  • Published (online): 28 March 2017
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Medicine, Dentistry and Health (Sheffield) > Department of Neuroscience (Sheffield)
Depositing User: Symplectic Sheffield
Date Deposited: 09 May 2017 08:36
Last Modified: 09 May 2017 08:36
Published Version: http://dx.doi.org/10.1038/sdata.2017.30
Status: Published
Publisher: Nature Publishing Group: Open Access Journals - Option C
Refereed: Yes
Identification Number: https://doi.org/10.1038/sdata.2017.30

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