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Deciphering tissue morphodynamics using bioimage informatics.

Alexandre C DufourAnneliene Hechtelt JonkerJean-Christophe Olivo-Marin
Published in: Philosophical transactions of the Royal Society of London. Series B, Biological sciences (2017)
In recent years developmental biology has greatly benefited from the latest advances in fluorescence microscopy techniques. Consequently, quantitative and automated analysis of this data is becoming a vital first step in the quest for novel insights into the various aspects of development. Here we present an introductory overview of the various image analysis methods proposed for developmental biology images, with particular attention to openly available software packages. These tools, as well as others to come, are rapidly paving the way towards standardized and reproducible bioimaging studies at the whole-tissue level. Reflecting on these achievements, we discuss the remaining challenges and the future endeavours lying ahead in the post-image analysis era.This article is part of the themed issue 'Systems morphodynamics: understanding the development of tissue hardware'.
Keyphrases
  • deep learning
  • single molecule
  • high resolution
  • optical coherence tomography
  • machine learning
  • electronic health record
  • big data
  • quantum dots
  • current status
  • mass spectrometry
  • living cells