Computational Tools for Stem Cell Biology

Qin Bian; Patrick Cahan

doi:10.1016/j.tibtech.2016.05.010

Computational Tools for Stem Cell Biology

Trends Biotechnol. 2016 Dec;34(12):993-1009. doi: 10.1016/j.tibtech.2016.05.010. Epub 2016 Jun 15.

Authors

Qin Bian¹, Patrick Cahan²

Affiliations

¹ Institute for Cell Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
² Institute for Cell Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA. Electronic address: [email protected].

Abstract

For over half a century, the field of developmental biology has leveraged computation to explore mechanisms of developmental processes. More recently, computational approaches have been critical in the translation of high throughput data into knowledge of both developmental and stem cell biology. In the past several years, a new subdiscipline of computational stem cell biology has emerged that synthesizes the modeling of systems-level aspects of stem cells with high-throughput molecular data. In this review, we provide an overview of this new field and pay particular attention to the impact that single cell transcriptomics is expected to have on our understanding of development and our ability to engineer cell fate.

Keywords: cell fate engineering; computational biology; network biology; single cell transcriptomics; stem cell biology.

Publication types

Review

MeSH terms

Animals
Cell Biology / trends*
Cells, Cultured
Computational Biology* / methods
Computational Biology* / trends
Humans
Mice
Stem Cell Research*
Stem Cells*

Grants and funding

K01 DK096013/DK/NIDDK NIH HHS/United States