Advances in mass spectrometry for clinical analysis: Data acquisition, interpretation and information integration

Bioinformatics has played an important role in analyzing chemical information acquired using mass spectrometry (MS) for large numbers of biological samples. Here we review the recent development of MS bioinformatics for clinical analysis, with aspects highlighted for data acquisition, interpretation and integration. It remains challenging in acquisition of chemical information from samples of extremely small volumes, such as in singlecell analysis or high-resolution MS imaging. For the analysis of complex biological samples by MS, it is usually difficult to obtain the signals of species of low abundance. Data dependent acquisition and data independent acquisition approaches have been developed to address these challenges. For clinical applications, artificial intelligence approaches have been applied into interpretation of omics data from disease diagnosis, while network atlas have also been developed to analyze biochemical relationships between organs. Finally, we also speculate the future development of MS bioinformatics regarding current clinical challenges.

Automated summary

This article reviews the recent development of MS bioinformatics in clinical analysis, focusing on data acquisition, interpretation, and integration. It also discusses the future development of MS bioinformatics in addressing current clinical challenges.