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

doi:10.1016/j.stem.2017.01.006

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

School of Cellular and Molecular Medicine

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

27 Citations (Scopus)

416 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 language	English
Pages (from-to)	157-160
Number of pages	4
Journal	Cell Stem Cell
Volume	20
Issue number	2
DOIs	https://doi.org/10.1016/j.stem.2017.01.006
Publication status	Published - 2 Feb 2017

Research Groups and Themes

Jean Golding

Keywords

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

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10.1016/j.stem.2017.01.006

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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

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title = "Big-Data-Driven Stem Cell Science and Tissue Engineering: Vision and Unique Opportunities",

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.",

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T2 - Vision and Unique Opportunities

AU - Del Sol, Antonio

AU - Thiesen, Hans J

AU - Imitola, Jaime

AU - Carazo Salas, Rafael E

PY - 2017/2/2

Y1 - 2017/2/2

N2 - 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.

AB - 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.

KW - Animals

KW - Computational Biology

KW - Humans

KW - Phenotype

KW - Science

KW - Statistics as Topic

KW - Stem Cells

KW - Tissue Engineering

KW - Journal Article

U2 - 10.1016/j.stem.2017.01.006

DO - 10.1016/j.stem.2017.01.006

M3 - Article (Academic Journal)

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SN - 1875-9777

VL - 20

SP - 157

EP - 160

JO - Cell Stem Cell

JF - Cell Stem Cell

IS - 2

ER -

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

Abstract

Research Groups and Themes

Keywords

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