Big-Data-Driven Stem Cell Science and Tissue Engineering: Vision and Unique Opportunities

Antonio Del Sol, Hans J Thiesen, Jaime Imitola, Rafael E Carazo Salas

Research output: Contribution to journal › Article (Academic Journal) › peer-review

290 Downloads (Pure)

Abstract

Achieving the promises of stem cell science to generate precise disease models and designer cell samples for personalized therapeutics will require harnessing pheno-genotypic cell-level data quantitatively and predictively in the lab and clinic. Those requirements could be met by developing a Big-Data-driven stem cell science strategy and community.

Original languageEnglish
Pages (from-to)157-160
Number of pages4
JournalCell Stem Cell
Volume20
Issue number2
DOIs
Publication statusPublished - 2 Feb 2017

Structured keywords

  • Jean Golding

Keywords

  • Animals
  • Computational Biology
  • Humans
  • Phenotype
  • Science
  • Statistics as Topic
  • Stem Cells
  • Tissue Engineering
  • Journal Article

Access to Document

  • Full-text PDF (accepted author manuscript)

    This is the author accepted manuscript (AAM). The final published version (version of record) is available online via Elsevier at https://www.sciencedirect.com/science/article/pii/S1934590917300073?via%3Dihub. Please refer to any applicable terms of use of the publisher.

    Accepted author manuscript, 352 KBLicence: CC BY-NC-ND

    Fingerprint Dive into the research topics of 'Big-Data-Driven Stem Cell Science and Tissue Engineering: Vision and Unique Opportunities'. Together they form a unique fingerprint.

    Cite this