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Stems cells, big data and compendium-based analyses for identifying cell types, signalling pathways and gene

Md Humayun Kabir1,2, Michael D O'Connor3,4

  • 1School of Medicine, Western Sydney University, Campbelltown, NSW, Australia.

Biophysical Reviews
|January 27, 2019
PubMed

Insights

This review explores how analyzing large datasets of gene and protein profiles from stem cells and organoids, using bioinformatics methods, can accelerate the discovery of new drug and cell therapies for diseases. Such compendium-based analyses enhance understanding of cell identity and disease pathways.

Area of Science:

  • Biotechnology
  • Genomics
  • Proteomics

Background:

  • Human pluripotent stem cells and organoids offer a valuable in vitro source for studying human cell types and tissues.
  • Understanding molecular mechanisms of normal and disease development is crucial for identifying new therapeutic targets.

Purpose of the Study:

  • To review how compendium-based analyses of 'omics' data can support stem cell technology applications in developing new therapies.
  • To highlight the role of molecular characterization in defining cell identity, signaling pathways, and gene networks.

Main Methods:

  • Utilizing big data ('omics') techniques like transcriptomics and proteomics for cell and tissue characterization.
  • Applying bioinformatics methods, including compendium-based analyses, to interpret large-scale gene and protein profiles.
  • Comparing sample profiles against reference compendia to understand biological states.

Main Results:

  • Compendium-based analyses facilitate robust definition of differentiated stem cell identity.
  • These methods aid in elucidating complex signaling pathways and target gene networks in both normal and diseased states.
  • The approach supports the application of stem cell technology for novel therapy development.

Conclusions:

  • Detailed molecular characterization using 'omics' and bioinformatics is key to advancing stem cell-based therapies.
  • Compendium-based analysis provides a powerful framework for drug and cell therapy target discovery.
  • This strategy enhances the translation of stem cell research into clinical applications.
Keywords:
BioinformaticsCompendiumGene regulatory networkGrowth factorPathwayPluripotent stem cellSignalling

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