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Towards 'end-to-end' analysis and understanding of biological timecourse data.

Siddhartha G JenaAlexander G GogliaBarbara Elizabeth Engelhardt
Published in: The Biochemical journal (2022)
Petabytes of increasingly complex and multidimensional live cell and tissue imaging data are generated every year. These videos hold large promise for understanding biology at a deep and fundamental level, as they capture single-cell and multicellular events occurring over time and space. However, the current modalities for analysis and mining of these data are scattered and user-specific, preventing more unified analyses from being performed over different datasets and obscuring possible scientific insights. Here, we propose a unified pipeline for storage, segmentation, analysis, and statistical parametrization of live cell imaging datasets.
Keyphrases
  • big data
  • single cell
  • high resolution
  • electronic health record
  • rna seq
  • machine learning
  • high throughput
  • mass spectrometry
  • photodynamic therapy