Computational Tools for Stem Cell Biology.
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.
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.
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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: patrick.cahan@jhmi.edu.
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D000818:Animals; D003585:Cell Biology / Q000639:trends*; D002478:Cells, Cultured; D019295:Computational Biology / Q000379:methods / Q000639:trends; D006801:Humans; D051379:Mice; D057905:Stem Cell Research; D013234:Stem Cells
cell fate engineering; computational biology; network biology; single cell transcriptomics; stem cell biology