Session Title: Data Science, Machine Learning, and Analytical Frameworks for Understanding the Heterogeneity of Cellular and Multicellular Systems

Session Summary:Cellular heterogeneity is a crucial factor and great challenge in understanding the behaviors and mechanisms of cellular and multicellular systems. To fully explore the heterogeneity, new measurement methods, analytical tools, and their integration are required. In this symposium, the speakers will present new approaches and their applications by using, e.g., imaging, bioinformatics, machine learning, and omics analysis.

Chairs/Speakers
サンプル
  • Katsuyuki Shiroguchi
  • (RIKEN)
サンプル
  • Susanne Rafelski
  • (Allen Institute for Cell Science)
Speakers
サンプル
  • Maria Brbic
  • (École polytechnique fédérale de Lausanne (EPFL))
サンプル
  • Vincenzo Vitelli
  • (University of Chicago)