Unsupervised learning approaches to characterizing heterogeneous samples using x-ray single-particle imaging

HIGHLIGHTS

• who: Yulong Zhuang and colleagues from the Max Planck Institute for the Structure and Dynamics of Matter, Hamburg, Germany, bCenter for Free-Electron Sciences, of Singapore, Singapore, fDepartment of Cell and Molecular Biology have published the Article: Unsupervised learning approaches to characterizing heterogeneous samples using X-ray single-particle imaging, in the Journal: IUCrJ (2022). 204-214 of /2022/
• what: The dataset discussed in the rest of this work was collected as part of the experiment described by Ayyer et_al , which the authors review in brief: In Fig 1(c), the authors show an example . . .
  

   

  

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