Deep learning-based pseudo-mass spectrometry imaging analysis for precision medicine

Abstract

Liquid chromatography–mass spectrometry (LC–MS)-based untargeted metabolomics provides systematic profiling of metabolic. Yet, its applications in precision medicine (disease diagnosis) have been limited by several challenges, including metabolite identification, information loss and low reproducibility. Here, we present the deep-learning-based Pseudo-Mass Spectrometry Imaging (deepPseudoMSI) project (https://www.deeppseudomsi.org/), which converts LC–MS raw data to pseudo-MS images and then processes them by deep learning for precision medicine, such as disease diagnosis. Extensive tests based on real data demonstrated the superiority of deepPseudoMSI over traditional approaches and the capacity of our method to achieve an accurate individualized diagnosis. Our framework lays the foundation for future metabolic-based precision medicine.

Publication
Briefings in Bioinformatics
Xiaotao SHEN/申小涛
Xiaotao SHEN/申小涛
Nanyang Assistant Professor

Metabolomics, Multi-omics, Bioinformatics, Systems Biology.

Prof. Wei Shao
Prof. Wei Shao
Assistant Professor
Dr. Liang Liang
Dr. Liang Liang
Research Scientist
Dr. Songjie Chen
Dr. Songjie Chen
Research Scientist
Prof. Sai Zhang
Prof. Sai Zhang
Assistant Professor