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Deep-learning model predicts how fruit flies form, cell by cell

20 hours ago
  • #deep learning
  • #cell dynamics
  • #developmental biology
  • MIT engineers developed a deep-learning model to predict minute-by-minute cell behavior during fruit fly embryo development.
  • The model tracks geometric properties of cells, such as position and neighbor contact, with 90% accuracy in predictions.
  • Potential applications include predicting development in more complex organisms and identifying early disease patterns like asthma and cancer.
  • The model uses a 'dual-graph' structure, combining point cloud and foam approaches to represent cell dynamics.
  • Trained on high-quality videos of fruit fly gastrulation, the model predicts cell folding, division, and neighbor interactions.
  • Future goals include applying the model to other species and human tissues, pending availability of high-quality data.