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Related Concept Videos

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Stem cell research aims to find ways to use stem cells to regenerate and repair cellular damage. Over time, most adult cells undergo the wear and tear of aging and lose their ability to divide and repair themselves. Stem cells do not display a particular morphology or function. Adult stem cells, which exist as a small subset of cells in most tissues, keep dividing and can differentiate into a number of specialized cells generally formed by that tissue. These cells enable the body to renew and...
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Quantitative Analysis of Protein Expression to Study Lineage Specification in Mouse Preimplantation Embryos
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Computational Tools for Stem Cell Biology.

Qin Bian1, Patrick Cahan1

  • 1Institute 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.

Trends in Biotechnology
|June 20, 2016
PubMed
Summary
This summary is machine-generated.

Computational approaches are revolutionizing developmental and stem cell biology. Single-cell transcriptomics is a key technology driving new insights and enabling cell fate engineering.

Keywords:
cell fate engineeringcomputational biologynetwork biologysingle cell transcriptomicsstem cell biology

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Area of Science:

  • Developmental Biology
  • Stem Cell Biology
  • Computational Biology

Background:

  • Computational methods have been integral to developmental biology for decades.
  • High-throughput data analysis has accelerated progress in developmental and stem cell biology.
  • A new subdiscipline, computational stem cell biology, integrates systems-level modeling with molecular data.

Purpose of the Study:

  • To provide an overview of the emerging field of computational stem cell biology.
  • To highlight the impact of single-cell transcriptomics on understanding development.
  • To discuss the potential of computational approaches in engineering cell fate.

Main Methods:

  • Review of existing literature and emerging trends in computational developmental and stem cell biology.
  • Focus on the integration of systems-level modeling with high-throughput molecular data.
  • Emphasis on the role and impact of single-cell transcriptomics.

Main Results:

  • The emergence of computational stem cell biology as a distinct field.
  • Significant advancements in understanding developmental processes through computational analysis.
  • Identification of single-cell transcriptomics as a transformative technology.

Conclusions:

  • Computational stem cell biology is a rapidly advancing field.
  • Single-cell transcriptomics is poised to significantly enhance our understanding of development.
  • This field holds great promise for the engineering of cell fate.