The project aims to automate and improve the manual analysis of liquid chromatography–mass spectrometry data for piptide detection.

  • Develop data processing pipeline to visualize and extract signal from liquid chromatography–mass spectrometry data of blood samples
  • Train machine learning models to classify whether blood samples contain certain targeted piptides based on mass spectrometry data