A brief review of signal processing issues in mass spectrometry-based proteomics studies

Mass spectrometry (MS) is frequently used in proteomics to conduct high-throughput experiments. In MS data analysis, low level signal processing tasks such as denoising, baseline correction and peak detection are involved to extract peptide related information for subsequent analysis. In the literature, numerous preprocessing methods have been described. We give a brief review of preprocessing methods and illustrate signal processing issues in MS data analysis.