Machine learning and computer vision approaches for phenotypic profiling.

Journal: The Journal of cell biology
Published Date: Jan 2, 2017

Abstract

With recent advances in high-throughput, automated microscopy, there has been an increased demand for effective computational strategies to analyze large-scale, image-based data. To this end, computer vision approaches have been applied to cell segmentation and feature extraction, whereas machine-learning approaches have been developed to aid in phenotypic classification and clustering of data acquired from biological images. Here, we provide an overview of the commonly used computer vision and machine-learning methods for generating and categorizing phenotypic profiles, highlighting the general biological utility of each approach.

Authors

  • Ben T Grys
    Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 3E1, Canada.
  • Dara S Lo
    Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 3E1, Canada.
  • Nil Sahin
    Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 3E1, Canada.
  • Oren Z Kraus
    Department of Electrical and Computer Engineering, University of Toronto, Toronto, M5S 2E4, Canada The Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, M5S 3E1, Canada.
  • Quaid Morris
    Department of Electrical and Computer Engineering, University of Toronto, Toronto, Ontario M5S 3G4, Canada. Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario M5S 3E1, Canada. Program on Genetic Networks and Program on Neural Computation & Adaptive Perception, Canadian Institute for Advanced Research, Toronto, Ontario M5G 1Z8, Canada. Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 1A8, Canada.
  • Charles Boone
    The Donnelly Centre, University of Toronto, Toronto, ON M5S3E1, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON M5S3E1, Canada.
  • Brenda J Andrews
    The Donnelly Centre, University of Toronto, Toronto, ON M5S3E1, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON M5S3E1, Canada. Electronic address: brenda.andrews@utoronto.ca.

Keywords

External Resources

Popular Topics
Recent Journals