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

24 Citations (Scopus)

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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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author = "{Del Sol}, Antonio and Thiesen, {Hans J} and Jaime Imitola and {Carazo Salas}, {Rafael E}",

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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)

C2 - 28157497

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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