NanoAI

Background

Optical microscopy has created an ever-lasting impact in life sciences. The last decade witnessed momentous progress in this field on the following fronts:

  • Achieving super-resolution, referred to as nanoscopy
  • Achieving high throughput via increasing imaging region through nanotechnological advances and chip-based M&N
  • Improving penetration depth for 3D microscopy
  • Long duration video imaging using better dyes and label-free microscopy techniques for living system studies

Within Norway itself, all Norwegian universities have made big infrastructure investments at their microscopy core facilities. However, the pace of development in M&N is suddenly witnessing a slump.

Interestingly, the slump is not related to the development potential but the inability to interpret and analyze the data thus generated and derive meaningful biological inferences from them. On one hand, imaging modality such as 4D nanoscopy holds a treasure of information for thorough study of disease and drug mechanisms. On the other hand, it is practically impossible for biologists to even visually scan the entire data, leave aside analyzing the information over large sample pools. ‘Looking for needle in haystack’ is a much simpler problem than filtering precise relevant information of nanoscale interactions interspersed sparsely in such data.