Login / Signup

Machine Learning for Single-Molecule Localization Microscopy: From Data Analysis to Quantification.

Jianli LiuYumian LiTailong ChenFa ZhangFan Xu
Published in: Analytical chemistry (2024)
Single-molecule localization microscopy (SMLM) is a versatile tool for realizing nanoscale imaging with visible light and providing unprecedented opportunities to observe bioprocesses. The integration of machine learning with SMLM enhances data analysis by improving efficiency and accuracy. This tutorial aims to provide a comprehensive overview of the data analysis process and theoretical aspects of SMLM, while also highlighting the typical applications of machine learning in this field. By leveraging advanced analytical techniques, SMLM is becoming a powerful quantitative analysis tool for biological research.
Keyphrases
  • data analysis
  • single molecule
  • machine learning
  • atomic force microscopy
  • visible light
  • artificial intelligence
  • living cells
  • big data
  • high resolution
  • deep learning
  • liquid chromatography
  • high throughput