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The challenges of big data.

Elaine R Mardis
Published in: Disease models & mechanisms (2017)
The largely untapped potential of big data analytics is a feeding frenzy that has been fueled by the production of many next-generation-sequencing-based data sets that are seeking to answer long-held questions about the biology of human diseases. Although these approaches are likely to be a powerful means of revealing new biological insights, there are a number of substantial challenges that currently hamper efforts to harness the power of big data. This Editorial outlines several such challenges as a means of illustrating that the path to big data revelations is paved with perils that the scientific community must overcome to pursue this important quest.
Keyphrases
  • big data
  • artificial intelligence
  • machine learning
  • mental health
  • endothelial cells
  • healthcare
  • quality improvement
  • copy number
  • risk assessment
  • genome wide
  • pluripotent stem cells