Mass spectrometry in proteomics

Abstract

This chapter focuses on issues that are related to analysis of high-throughput proteomics and metabolomics data generated by studies employing mass spectrometry (MS). It uses the linear models for microarray data (limma) method to illustrate differential expression analysis. When applying to proteomics data, limma fits linear models on the data along with empirical Bayes estimators to determine differential expression of proteins. The chapter also summarizes examples of specific applications in the fields of qualitative and quantitative environmental and biological analysis including characteristics of current trends in this area. The unique capabilities of inductively coupled plasma MS coupled to other techniques are demonstrated, and few selected recent developments in this field are discussed in more details. The chapter further describes basic concepts and future prospects of MS applications in forensic research. Not only this subject includes typical investigations on the crime scene but also anti-doping research, forgery in art, anti-terror actions, and counterfeit medicines, among others.