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Morphomics via next-generation electron microscopy.

Raku SonKenji YamazawaAkiko OguchiMitsuo SugaMasaru TamuraMotoko YanagitaYasuhiro MurakawaSatoshi Kume
Published in: Journal of molecular cell biology (2023)
The living body is composed of innumerable fine and complex structures. Although these structures have been studied in the past, a vast amount of information pertaining to them still remains unknown. When attempting to observe these ultra-structures, the use of electron microscopy (EM) has become indispensable. However, conventional EM settings are limited to a narrow tissue area, which can bias observations. Recently, new trends in EM research have emerged that provide coverage of far broader, nano-scale fields of view for two-dimensional wide areas and three-dimensional large volumes. Moreover, cutting-edge bioimage informatics conducted via deep learning has accelerated the quantification of complex morphological bioimages. Taken together, these technological and analytical advances have led to the comprehensive acquisition and quantification of cellular morphology, which now arises as a new omics science termed 'morphomics'.
Keyphrases
  • electron microscopy
  • high resolution
  • deep learning
  • public health
  • air pollution
  • machine learning
  • artificial intelligence
  • mass spectrometry
  • healthcare
  • single cell
  • electronic health record
  • big data
  • health insurance