Deep learning models will shape the future of stem cell research.

Journal: Stem cell reports
Published Date:

Abstract

Our ability to understand and control stem cell biology is being augmented by developments on two fronts, our ability to collect more data describing cell state and our capability to comprehend these data using deep learning models. Here we consider the impact deep learning will have in the future of stem cell research. We explore the importance of generating data suitable for these methods, the requirement for close collaboration between experimental and computational researchers, and the challenges we face to do this fairly and effectively. Achieving this will ensure that the resulting deep learning models are biologically meaningful and computationally tractable.

Authors

  • John F Ouyang
    Duke-NUS Medical School, Program in Cardiovascular and Metabolic Disorders (CVMD) and Centre for Computational Biology (CCB), Singapore, Singapore.
  • Sonia Chothani
    Duke-NUS Medical School, Program in Cardiovascular and Metabolic Disorders (CVMD) and Centre for Computational Biology (CCB), Singapore, Singapore.
  • Owen J L Rackham
    Duke-NUS Medical School, Program in Cardiovascular and Metabolic Disorders (CVMD) and Centre for Computational Biology (CCB), Singapore, Singapore; School of Biological Sciences, University of Southampton, Southampton, UK; The Alan Turing Institute, The British Library, London, UK. Electronic address: o.j.l.rackham@soton.ac.uk.